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(v1.8.1) prerelease 1.8.1

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dr. M.S. (Matthijs) Berends 2022-03-14 16:36:10 +01:00
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR Package: AMR
Version: 1.8.0.9005 Version: 1.8.1
Date: 2022-03-10 Date: 2022-03-14
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by data analysis and to work with microbial and antimicrobial properties by

4
NEWS.md
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@ -1,5 +1,5 @@
# `AMR` 1.8.0.9005 # `AMR` 1.8.1
## <small>Last updated: 10 March 2022</small>
All functions in this package are considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months. All functions in this package are considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months.

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R/zzz.R
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@ -116,21 +116,7 @@ if (utf8_supported && !is_latex) {
# Helper functions -------------------------------------------------------- # Helper functions --------------------------------------------------------
create_AB_lookup <- function() { create_AB_lookup <- function() {
AB_lookup <- AMR::antibiotics cbind(AMR::antibiotics, AB_LOOKUP)
AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
AB_lookup$generalised_all <- unname(lapply(as.list(as.data.frame(t(AB_lookup[,
c("ab", "atc", "cid", "name",
colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]),
drop = FALSE]),
stringsAsFactors = FALSE)),
function(x) {
x <- generalise_antibiotic_name(unname(unlist(x)))
x[x != ""]
}))
AB_lookup
} }
create_MO_lookup <- function() { create_MO_lookup <- function() {
@ -145,12 +131,7 @@ create_MO_lookup <- function() {
MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5 MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5
# use this paste instead of `fullname` to work with Viridans Group Streptococci, etc. # use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
MO_lookup$fullname_lower <- tolower(trimws(paste(MO_lookup$genus, MO_lookup$fullname_lower <- MO_FULLNAME_LOWER
MO_lookup$species,
MO_lookup$subspecies)))
ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname, perl = TRUE)
MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname"])
MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
# add a column with only "e coli" like combinations # add a column with only "e coli" like combinations
MO_lookup$g_species <- gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO_lookup$fullname_lower, perl = TRUE) MO_lookup$g_species <- gsub("^([a-z])[a-z]+ ([a-z]+) ?.*", "\\1 \\2", MO_lookup$fullname_lower, perl = TRUE)

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data-raw/_internals.R
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@ -122,9 +122,21 @@ create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
"mo", drop = TRUE] "mo", drop = TRUE]
} }
} }
create_MO_fullname_lower <- function() {
MO_lookup <- AMR::microorganisms
# use this paste instead of `fullname` to work with Viridans Group Streptococci, etc.
MO_lookup$fullname_lower <- tolower(trimws(paste(MO_lookup$genus,
MO_lookup$species,
MO_lookup$subspecies)))
ind <- MO_lookup$genus == "" | grepl("^[(]unknown ", MO_lookup$fullname, perl = TRUE)
MO_lookup[ind, "fullname_lower"] <- tolower(MO_lookup[ind, "fullname"])
MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
MO_lookup$fullname_lower
}
MO_CONS <- create_species_cons_cops("CoNS") MO_CONS <- create_species_cons_cops("CoNS")
MO_COPS <- create_species_cons_cops("CoPS") MO_COPS <- create_species_cons_cops("CoPS")
MO_STREP_ABCG <- as.mo(MO_lookup[which(MO_lookup$genus == "Streptococcus"), "mo", drop = TRUE], Lancefield = TRUE) %in% c("B_STRPT_GRPA", "B_STRPT_GRPB", "B_STRPT_GRPC", "B_STRPT_GRPG") MO_STREP_ABCG <- as.mo(MO_lookup[which(MO_lookup$genus == "Streptococcus"), "mo", drop = TRUE], Lancefield = TRUE) %in% c("B_STRPT_GRPA", "B_STRPT_GRPB", "B_STRPT_GRPC", "B_STRPT_GRPG")
MO_FULLNAME_LOWER <- create_MO_fullname_lower()
# antibiotic groups # antibiotic groups
# (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv) # (these will also be used for eucast_rules() and understanding data-raw/eucast_rules.tsv)
@ -160,6 +172,24 @@ AB_BETALACTAMS <- c(AB_PENICILLINS, AB_CEPHALOSPORINS, AB_CARBAPENEMS)
# this will be used for documentation: # this will be used for documentation:
DEFINED_AB_GROUPS <- ls(envir = globalenv()) DEFINED_AB_GROUPS <- ls(envir = globalenv())
DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab] DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab]
create_AB_lookup <- function() {
AB_lookup <- AMR::antibiotics
AB_lookup$generalised_name <- generalise_antibiotic_name(AB_lookup$name)
AB_lookup$generalised_synonyms <- lapply(AB_lookup$synonyms, generalise_antibiotic_name)
AB_lookup$generalised_abbreviations <- lapply(AB_lookup$abbreviations, generalise_antibiotic_name)
AB_lookup$generalised_loinc <- lapply(AB_lookup$loinc, generalise_antibiotic_name)
AB_lookup$generalised_all <- unname(lapply(as.list(as.data.frame(t(AB_lookup[,
c("ab", "atc", "cid", "name",
colnames(AB_lookup)[colnames(AB_lookup) %like% "generalised"]),
drop = FALSE]),
stringsAsFactors = FALSE)),
function(x) {
x <- generalise_antibiotic_name(unname(unlist(x)))
x[x != ""]
}))
AB_lookup[, colnames(AB_lookup)[colnames(AB_lookup) %like% "^generalised"]]
}
AB_LOOKUP <- create_AB_lookup()
# Export to package as internal data ---- # Export to package as internal data ----
usethis::use_data(EUCAST_RULES_DF, usethis::use_data(EUCAST_RULES_DF,
@ -169,6 +199,8 @@ usethis::use_data(EUCAST_RULES_DF,
MO_CONS, MO_CONS,
MO_COPS, MO_COPS,
MO_STREP_ABCG, MO_STREP_ABCG,
MO_FULLNAME_LOWER,
AB_LOOKUP,
AB_AMINOGLYCOSIDES, AB_AMINOGLYCOSIDES,
AB_AMINOPENICILLINS, AB_AMINOPENICILLINS,
AB_ANTIFUNGALS, AB_ANTIFUNGALS,

2
docs/404.html
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@ -43,7 +43,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a> <a class="navbar-link" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/LICENSE-text.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

560
docs/articles/AMR.html
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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -192,7 +192,7 @@
<h4 data-toc-skip class="author">Dr Matthijs <h4 data-toc-skip class="author">Dr Matthijs
Berends</h4> Berends</h4>
<h4 data-toc-skip class="date">10 March 2022</h4> <h4 data-toc-skip class="date">14 March 2022</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small> <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
<div class="hidden name"><code>AMR.Rmd</code></div> <div class="hidden name"><code>AMR.Rmd</code></div>
@ -205,7 +205,7 @@ Berends</h4>
website update since they are based on randomly created values and the website update since they are based on randomly created values and the
page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
Markdown</a>. However, the methodology remains unchanged. This page was Markdown</a>. However, the methodology remains unchanged. This page was
generated on 10 March 2022.</p> generated on 14 March 2022.</p>
<div class="section level2"> <div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2> </h2>
@ -261,21 +261,21 @@ make the structure of your data generally look like this:</p>
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2022-03-10</td> <td align="center">2022-03-14</td>
<td align="center">abcd</td> <td align="center">abcd</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2022-03-10</td> <td align="center">2022-03-14</td>
<td align="center">abcd</td> <td align="center">abcd</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">2022-03-10</td> <td align="center">2022-03-14</td>
<td align="center">efgh</td> <td align="center">efgh</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">R</td> <td align="center">R</td>
@ -392,12 +392,12 @@ data set:</p>
<col width="13%"> <col width="13%">
<col width="13%"> <col width="13%">
<col width="13%"> <col width="13%">
<col width="26%"> <col width="28%">
<col width="5%"> <col width="5%">
<col width="5%"> <col width="5%">
<col width="5%"> <col width="5%">
<col width="5%"> <col width="5%">
<col width="9%"> <col width="8%">
</colgroup> </colgroup>
<thead><tr class="header"> <thead><tr class="header">
<th align="center">date</th> <th align="center">date</th>
@ -412,21 +412,21 @@ data set:</p>
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2018-01-01</td> <td align="center">2014-06-27</td>
<td align="center">Z9</td> <td align="center">G7</td>
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td> <td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">F</td> <td align="center">S</td>
<td align="center">M</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2010-04-06</td> <td align="center">2014-02-01</td>
<td align="center">G1</td> <td align="center">H10</td>
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">Staphylococcus aureus</td> <td align="center">Streptococcus pneumoniae</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -434,47 +434,47 @@ data set:</p>
<td align="center">M</td> <td align="center">M</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">2016-12-08</td> <td align="center">2011-05-09</td>
<td align="center">I1</td> <td align="center">V2</td>
<td align="center">Hospital B</td> <td align="center">Hospital C</td>
<td align="center">Staphylococcus aureus</td> <td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">I</td> <td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2016-09-06</td>
<td align="center">V10</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2014-04-11</td>
<td align="center">M4</td>
<td align="center">Hospital D</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">M</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2015-12-05</td> <td align="center">2017-06-26</td>
<td align="center">R10</td> <td align="center">D7</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2014-11-30</td>
<td align="center">N6</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2012-10-12</td>
<td align="center">I6</td>
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">Escherichia coli</td> <td align="center">Escherichia coli</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">R</td>
<td align="center">M</td> <td align="center">M</td>
</tr> </tr>
</tbody> </tbody>
@ -511,16 +511,16 @@ Longest: 1</p>
<tr class="odd"> <tr class="odd">
<td align="left">1</td> <td align="left">1</td>
<td align="left">M</td> <td align="left">M</td>
<td align="right">10,395</td> <td align="right">10,413</td>
<td align="right">51.98%</td> <td align="right">52.07%</td>
<td align="right">10,395</td> <td align="right">10,413</td>
<td align="right">51.98%</td> <td align="right">52.07%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">2</td> <td align="left">2</td>
<td align="left">F</td> <td align="left">F</td>
<td align="right">9,605</td> <td align="right">9,587</td>
<td align="right">48.03%</td> <td align="right">47.94%</td>
<td align="right">20,000</td> <td align="right">20,000</td>
<td align="right">100.00%</td> <td align="right">100.00%</td>
</tr> </tr>
@ -630,9 +630,9 @@ takes into account the antimicrobial susceptibility test results using
<span class="co"># ℹ Using column 'patient_id' as input for `col_patient_id`.</span> <span class="co"># ℹ Using column 'patient_id' as input for `col_patient_id`.</span>
<span class="co"># Basing inclusion on all antimicrobial results, using a points threshold of</span> <span class="co"># Basing inclusion on all antimicrobial results, using a points threshold of</span>
<span class="co"># 2</span> <span class="co"># 2</span>
<span class="co"># =&gt; Found 10,713 'phenotype-based' first isolates (53.6% of total where a</span> <span class="co"># =&gt; Found 10,616 'phenotype-based' first isolates (53.1% of total where a</span>
<span class="co"># microbial ID was available)</span></code></pre></div> <span class="co"># microbial ID was available)</span></code></pre></div>
<p>So only 53.6% is suitable for resistance analysis! We can now filter <p>So only 53.1% is suitable for resistance analysis! We can now filter
on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> function, also from the on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> function, also from the
<code>dplyr</code> package:</p> <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
@ -642,7 +642,7 @@ on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html"
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">data_1st</span> <span class="op">&lt;-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <code class="sourceCode R"><span class="va">data_1st</span> <span class="op">&lt;-</span> <span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
<span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span></code></pre></div> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span></code></pre></div>
<p>So we end up with 10,713 isolates for analysis. Now our data looks <p>So we end up with 10,616 isolates for analysis. Now our data looks
like:</p> like:</p>
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data_1st</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data_1st</span><span class="op">)</span></code></pre></div>
@ -681,13 +681,93 @@ like:</p>
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="left">3</td> <td align="left">1</td>
<td align="center">2016-12-08</td> <td align="center">2014-06-27</td>
<td align="center">I1</td> <td align="center">G7</td>
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">B_STPHY_AURS</td> <td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="center">2014-02-01</td>
<td align="center">H10</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">I</td> <td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="center">2011-05-09</td>
<td align="center">V2</td>
<td align="center">Hospital C</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="left">6</td>
<td align="center">2017-06-26</td>
<td align="center">D7</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="left">7</td>
<td align="center">2013-09-19</td>
<td align="center">U8</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="left">9</td>
<td align="center">2012-08-01</td>
<td align="center">I2</td>
<td align="center">Hospital D</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">M</td> <td align="center">M</td>
@ -696,86 +776,6 @@ like:</p>
<td align="center">aureus</td> <td align="center">aureus</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even">
<td align="left">5</td>
<td align="center">2014-11-30</td>
<td align="center">N6</td>
<td align="center">Hospital C</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="left">8</td>
<td align="center">2016-12-03</td>
<td align="center">J3</td>
<td align="center">Hospital A</td>
<td align="center">B_KLBSL_PNMN</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Klebsiella</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="left">9</td>
<td align="center">2010-04-28</td>
<td align="center">J10</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="left">15</td>
<td align="center">2010-08-04</td>
<td align="center">L1</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="left">17</td>
<td align="center">2014-04-28</td>
<td align="center">Q5</td>
<td align="center">Hospital C</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
</tbody> </tbody>
</table> </table>
<p>Time for the analysis!</p> <p>Time for the analysis!</p>
@ -809,8 +809,8 @@ readable:</p>
<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">genus</span>, <span class="va">species</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq</a></span><span class="op">(</span><span class="va">genus</span>, <span class="va">species</span><span class="op">)</span></code></pre></div>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table</strong></p>
<p>Class: character<br> <p>Class: character<br>
Length: 10,713<br> Length: 10,616<br>
Available: 10,713 (100%, NA: 0 = 0%)<br> Available: 10,616 (100%, NA: 0 = 0%)<br>
Unique: 4</p> Unique: 4</p>
<p>Shortest: 16<br> <p>Shortest: 16<br>
Longest: 24</p> Longest: 24</p>
@ -835,33 +835,33 @@ Longest: 24</p>
<tr class="odd"> <tr class="odd">
<td align="left">1</td> <td align="left">1</td>
<td align="left">Escherichia coli</td> <td align="left">Escherichia coli</td>
<td align="right">4,596</td> <td align="right">4,673</td>
<td align="right">42.90%</td> <td align="right">44.02%</td>
<td align="right">4,596</td> <td align="right">4,673</td>
<td align="right">42.90%</td> <td align="right">44.02%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">2</td> <td align="left">2</td>
<td align="left">Staphylococcus aureus</td> <td align="left">Staphylococcus aureus</td>
<td align="right">2,805</td> <td align="right">2,710</td>
<td align="right">26.18%</td> <td align="right">25.53%</td>
<td align="right">7,401</td> <td align="right">7,383</td>
<td align="right">69.08%</td> <td align="right">69.55%</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">3</td> <td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td> <td align="left">Streptococcus pneumoniae</td>
<td align="right">2,128</td> <td align="right">2,068</td>
<td align="right">19.86%</td> <td align="right">19.48%</td>
<td align="right">9,529</td> <td align="right">9,451</td>
<td align="right">88.95%</td> <td align="right">89.03%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">4</td> <td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td> <td align="left">Klebsiella pneumoniae</td>
<td align="right">1,184</td> <td align="right">1,165</td>
<td align="right">11.05%</td> <td align="right">10.97%</td>
<td align="right">10,713</td> <td align="right">10,616</td>
<td align="right">100.00%</td> <td align="right">100.00%</td>
</tr> </tr>
</tbody> </tbody>
@ -910,23 +910,8 @@ antibiotic class they are in:</p>
</tr></thead> </tr></thead>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">2016-12-03</td> <td align="center">2014-02-01</td>
<td align="center">J3</td> <td align="center">H10</td>
<td align="center">Hospital A</td>
<td align="center">B_KLBSL_PNMN</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Klebsiella</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2010-08-04</td>
<td align="center">L1</td>
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td> <td align="center">B_STRPT_PNMN</td>
<td align="center">R</td> <td align="center">R</td>
@ -939,28 +924,13 @@ antibiotic class they are in:</p>
<td align="center">pneumoniae</td> <td align="center">pneumoniae</td>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd">
<td align="center">2014-04-28</td>
<td align="center">Q5</td>
<td align="center">Hospital C</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even"> <tr class="even">
<td align="center">2015-05-06</td> <td align="center">2017-06-26</td>
<td align="center">L9</td> <td align="center">D7</td>
<td align="center">Hospital D</td> <td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td> <td align="center">B_ESCHR_COLI</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">M</td> <td align="center">M</td>
@ -970,14 +940,14 @@ antibiotic class they are in:</p>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">2010-09-03</td> <td align="center">2012-06-14</td>
<td align="center">M3</td> <td align="center">G7</td>
<td align="center">Hospital A</td> <td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td> <td align="center">B_STRPT_PNMN</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">R</td> <td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td> <td align="center">M</td>
<td align="center">Gram-positive</td> <td align="center">Gram-positive</td>
<td align="center">Streptococcus</td> <td align="center">Streptococcus</td>
@ -985,9 +955,39 @@ antibiotic class they are in:</p>
<td align="center">TRUE</td> <td align="center">TRUE</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">2011-10-13</td> <td align="center">2016-05-08</td>
<td align="center">D4</td> <td align="center">K4</td>
<td align="center">Hospital C</td> <td align="center">Hospital D</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">2015-03-03</td>
<td align="center">G4</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2016-11-20</td>
<td align="center">D1</td>
<td align="center">Hospital A</td>
<td align="center">B_STRPT_PNMN</td> <td align="center">B_STRPT_PNMN</td>
<td align="center">S</td> <td align="center">S</td>
<td align="center">S</td> <td align="center">S</td>
@ -1022,50 +1022,50 @@ different bug/drug combinations, you can use the
<tr class="odd"> <tr class="odd">
<td align="center">E. coli</td> <td align="center">E. coli</td>
<td align="center">AMX</td> <td align="center">AMX</td>
<td align="center">2197</td> <td align="center">2205</td>
<td align="center">113</td> <td align="center">120</td>
<td align="center">2286</td> <td align="center">2348</td>
<td align="center">4596</td> <td align="center">4673</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">E. coli</td> <td align="center">E. coli</td>
<td align="center">AMC</td> <td align="center">AMC</td>
<td align="center">3395</td> <td align="center">3462</td>
<td align="center">149</td> <td align="center">158</td>
<td align="center">1052</td> <td align="center">1053</td>
<td align="center">4596</td> <td align="center">4673</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">E. coli</td> <td align="center">E. coli</td>
<td align="center">CIP</td> <td align="center">CIP</td>
<td align="center">3341</td> <td align="center">3424</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">1255</td> <td align="center">1249</td>
<td align="center">4596</td> <td align="center">4673</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">E. coli</td> <td align="center">E. coli</td>
<td align="center">GEN</td> <td align="center">GEN</td>
<td align="center">3997</td> <td align="center">4079</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">599</td> <td align="center">594</td>
<td align="center">4596</td> <td align="center">4673</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">K. pneumoniae</td> <td align="center">K. pneumoniae</td>
<td align="center">AMX</td> <td align="center">AMX</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">1184</td> <td align="center">1165</td>
<td align="center">1184</td> <td align="center">1165</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">K. pneumoniae</td> <td align="center">K. pneumoniae</td>
<td align="center">AMC</td> <td align="center">AMC</td>
<td align="center">917</td> <td align="center">940</td>
<td align="center">43</td> <td align="center">45</td>
<td align="center">224</td> <td align="center">180</td>
<td align="center">1184</td> <td align="center">1165</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1088,34 +1088,34 @@ different bug/drug combinations, you can use the
<tr class="odd"> <tr class="odd">
<td align="center">E. coli</td> <td align="center">E. coli</td>
<td align="center">GEN</td> <td align="center">GEN</td>
<td align="center">3997</td> <td align="center">4079</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">599</td> <td align="center">594</td>
<td align="center">4596</td> <td align="center">4673</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">K. pneumoniae</td> <td align="center">K. pneumoniae</td>
<td align="center">GEN</td> <td align="center">GEN</td>
<td align="center">1070</td> <td align="center">1058</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">114</td> <td align="center">107</td>
<td align="center">1184</td> <td align="center">1165</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">S. aureus</td> <td align="center">S. aureus</td>
<td align="center">GEN</td> <td align="center">GEN</td>
<td align="center">2476</td> <td align="center">2429</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">329</td> <td align="center">281</td>
<td align="center">2805</td> <td align="center">2710</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">S. pneumoniae</td> <td align="center">S. pneumoniae</td>
<td align="center">GEN</td> <td align="center">GEN</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">0</td> <td align="center">0</td>
<td align="center">2128</td> <td align="center">2068</td>
<td align="center">2128</td> <td align="center">2068</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1147,7 +1147,7 @@ I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equa
own:</p> own:</p>
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span> <code class="sourceCode R"><span class="va">data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span>
<span class="co"># [1] 0.5424251</span></code></pre></div> <span class="co"># [1] 0.5451206</span></code></pre></div>
<p>Or can be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and <p>Or can be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and
<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, both from the <code>dplyr</code> package:</p> <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
@ -1162,19 +1162,19 @@ own:</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">0.5412355</td> <td align="center">0.5451684</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">0.5406417</td> <td align="center">0.5455526</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital C</td> <td align="center">Hospital C</td>
<td align="center">0.5450746</td> <td align="center">0.5361146</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital D</td> <td align="center">Hospital D</td>
<td align="center">0.5452821</td> <td align="center">0.5511069</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1197,23 +1197,23 @@ all isolates available for every group (i.e. values S, I or R):</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital A</td> <td align="center">Hospital A</td>
<td align="center">0.5412355</td> <td align="center">0.5451684</td>
<td align="center">3189</td> <td align="center">3177</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital B</td> <td align="center">Hospital B</td>
<td align="center">0.5406417</td> <td align="center">0.5455526</td>
<td align="center">3740</td> <td align="center">3710</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">Hospital C</td> <td align="center">Hospital C</td>
<td align="center">0.5450746</td> <td align="center">0.5361146</td>
<td align="center">1675</td> <td align="center">1606</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Hospital D</td> <td align="center">Hospital D</td>
<td align="center">0.5452821</td> <td align="center">0.5511069</td>
<td align="center">2109</td> <td align="center">2123</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1236,27 +1236,27 @@ therapies very easily:</p>
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="center">Escherichia</td> <td align="center">Escherichia</td>
<td align="center">0.7711053</td> <td align="center">0.7746630</td>
<td align="center">0.8696693</td> <td align="center">0.8728868</td>
<td align="center">0.9738903</td> <td align="center">0.9779585</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Klebsiella</td> <td align="center">Klebsiella</td>
<td align="center">0.8108108</td> <td align="center">0.8454936</td>
<td align="center">0.9037162</td> <td align="center">0.9081545</td>
<td align="center">0.9805743</td> <td align="center">0.9896996</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="center">Staphylococcus</td> <td align="center">Staphylococcus</td>
<td align="center">0.7907308</td> <td align="center">0.7874539</td>
<td align="center">0.8827094</td> <td align="center">0.8963100</td>
<td align="center">0.9732620</td> <td align="center">0.9797048</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="center">Streptococcus</td> <td align="center">Streptococcus</td>
<td align="center">0.5324248</td> <td align="center">0.5357834</td>
<td align="center">0.0000000</td> <td align="center">0.0000000</td>
<td align="center">0.5324248</td> <td align="center">0.5357834</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1284,23 +1284,23 @@ classes, use a antibiotic class selector such as
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td align="left">Hospital A</td> <td align="left">Hospital A</td>
<td align="right">54.1%</td> <td align="right">54.5%</td>
<td align="right">27.2%</td> <td align="right">26.5%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Hospital B</td> <td align="left">Hospital B</td>
<td align="right">54.1%</td> <td align="right">54.6%</td>
<td align="right">27.4%</td> <td align="right">25.9%</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">Hospital C</td> <td align="left">Hospital C</td>
<td align="right">54.5%</td> <td align="right">53.6%</td>
<td align="right">25.0%</td> <td align="right">25.3%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">Hospital D</td> <td align="left">Hospital D</td>
<td align="right">54.5%</td> <td align="right">55.1%</td>
<td align="right">25.9%</td> <td align="right">26.4%</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
@ -1402,16 +1402,18 @@ classes) <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code>:</p>
<code class="sourceCode R"><span class="va">mic_values</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span> <code class="sourceCode R"><span class="va">mic_values</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/random.html">random_mic</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
<span class="va">mic_values</span> <span class="va">mic_values</span>
<span class="co"># Class &lt;mic&gt;</span> <span class="co"># Class &lt;mic&gt;</span>
<span class="co"># [1] 1 128 256 8 64 0.5 4 32 16 0.025 </span> <span class="co"># [1] 0.125 8 &lt;=0.001 0.002 64 &gt;=256 0.005 4 0.5 </span>
<span class="co"># [11] 16 0.025 2 1 0.025 64 32 32 8 0.5 </span> <span class="co"># [10] 0.002 &lt;=0.001 0.01 0.01 0.25 128 0.002 &gt;=256 0.005 </span>
<span class="co"># [21] 0.025 256 1 0.005 0.001 1 16 0.025 1 0.002 </span> <span class="co"># [19] 4 0.25 &gt;=256 0.0625 64 0.002 0.0625 0.0625 2 </span>
<span class="co"># [31] 0.0625 0.125 0.0625 0.01 0.01 4 64 0.002 0.25 128 </span> <span class="co"># [28] 32 16 32 0.5 &gt;=256 32 &lt;=0.001 &gt;=256 64 </span>
<span class="co"># [41] 64 16 16 0.005 0.125 0.5 0.5 0.5 1 32 </span> <span class="co"># [37] &lt;=0.001 32 &gt;=256 0.0625 0.025 8 1 0.002 &lt;=0.001</span>
<span class="co"># [51] 0.25 0.125 8 8 0.25 256 2 256 0.125 128 </span> <span class="co"># [46] 0.01 2 0.005 128 0.025 0.125 0.5 0.01 0.0625 </span>
<span class="co"># [61] 0.001 0.001 32 4 16 256 2 0.01 4 8 </span> <span class="co"># [55] 2 0.005 64 2 2 4 8 4 0.5 </span>
<span class="co"># [71] 0.001 0.125 1 0.01 0.25 8 1 0.005 64 0.025 </span> <span class="co"># [64] 16 &lt;=0.001 0.25 16 0.002 1 64 0.025 4 </span>
<span class="co"># [81] 256 16 1 64 8 32 0.002 0.01 4 0.0625</span> <span class="co"># [73] 0.005 0.002 0.01 32 0.025 0.01 0.025 0.025 64 </span>
<span class="co"># [91] 0.025 0.002 0.005 0.01 256 0.125 16 1 0.5 0.01</span></code></pre></div> <span class="co"># [82] 0.01 4 0.025 1 0.025 8 2 32 0.0625 </span>
<span class="co"># [91] 128 0.0625 16 128 4 &gt;=256 64 0.125 &lt;=0.001</span>
<span class="co"># [100] 0.25</span></code></pre></div>
<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># base R:</span> <code class="sourceCode R"><span class="co"># base R:</span>
<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">mic_values</span><span class="op">)</span></code></pre></div> <span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">mic_values</span><span class="op">)</span></code></pre></div>
@ -1447,10 +1449,10 @@ plotting:</p>
<span class="co"># coli). Run `mo_uncertainties()` to review this.</span> <span class="co"># coli). Run `mo_uncertainties()` to review this.</span>
<span class="va">disk_values</span> <span class="va">disk_values</span>
<span class="co"># Class &lt;disk&gt;</span> <span class="co"># Class &lt;disk&gt;</span>
<span class="co"># [1] 28 24 25 16 19 16 27 30 25 19 27 24 27 26 18 28 21 25 22 25 19 21 19 29 31</span> <span class="co"># [1] 29 26 29 16 27 26 25 16 25 27 21 26 29 17 21 18 27 18 31 29 19 23 25 20 30</span>
<span class="co"># [26] 28 25 16 22 16 26 28 20 18 27 26 29 28 19 26 30 21 30 27 28 18 27 28 31 18</span> <span class="co"># [26] 22 28 18 21 29 30 29 23 27 16 16 28 18 16 22 29 31 17 27 21 28 29 24 19 24</span>
<span class="co"># [51] 29 22 17 22 22 19 19 25 19 24 16 22 16 28 22 27 26 25 20 25 26 19 18 17 27</span> <span class="co"># [51] 28 27 16 23 30 18 30 22 21 22 16 20 16 25 28 29 23 29 30 17 29 17 18 24 21</span>
<span class="co"># [76] 24 24 18 16 28 29 25 16 23 28 29 16 19 29 17 21 26 17 19 25 23 17 22 25 20</span></code></pre></div> <span class="co"># [76] 17 18 18 29 18 25 16 18 27 26 28 25 20 21 18 18 24 30 18 18 24 22 24 25 28</span></code></pre></div>
<div class="sourceCode" id="cb43"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb43"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># base R:</span> <code class="sourceCode R"><span class="co"># base R:</span>
<span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">disk_values</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span></code></pre></div> <span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">disk_values</span>, mo <span class="op">=</span> <span class="st">"E. coli"</span>, ab <span class="op">=</span> <span class="st">"cipro"</span><span class="op">)</span></code></pre></div>

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52
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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -201,18 +201,39 @@
<div class="section level2"> <div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2> </h2>
<p>What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">on their website</a>:</p> <p>What are EUCAST rules? The European Committee on Antimicrobial
Susceptibility Testing (EUCAST) states <a href="https://www.eucast.org/expert_rules_and_intrinsic_resistance/" class="external-link">on
their website</a>:</p>
<blockquote> <blockquote>
<p><em>EUCAST expert rules are a tabulated collection of expert knowledge on intrinsic resistances, exceptional resistance phenotypes and interpretive rules that may be applied to antimicrobial susceptibility testing in order to reduce errors and make appropriate recommendations for reporting particular resistances.</em></p> <p><em>EUCAST expert rules are a tabulated collection of expert
knowledge on intrinsic resistances, exceptional resistance phenotypes
and interpretive rules that may be applied to antimicrobial
susceptibility testing in order to reduce errors and make appropriate
recommendations for reporting particular resistances.</em></p>
</blockquote> </blockquote>
<p>In Europe, a lot of medical microbiological laboratories already apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008" class="external-link">Brown <em>et al.</em>, 2015</a>). Our package features their latest insights on intrinsic resistance and unusual phenotypes (v3.3, 2021).</p> <p>In Europe, a lot of medical microbiological laboratories already
<p>Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this purpose can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R in isolates when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p> apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008" class="external-link">Brown
<em>et al.</em>, 2015</a>). Our package features their latest insights
on intrinsic resistance and unusual phenotypes (v3.3, 2021).</p>
<p>Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this
purpose can also apply additional rules, like forcing
<help title="ATC: J01CA01">ampicillin</help> = R in isolates when
<help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
</div> </div>
<div class="section level2"> <div class="section level2">
<h2 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a> <h2 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a>
</h2> </h2>
<p>These rules can be used to discard impossible bug-drug combinations in your data. For example, <em>Klebsiella</em> produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, practically every strain of <em>Klebsiella</em> is resistant to ampicillin.</p> <p>These rules can be used to discard impossible bug-drug combinations
<p>Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p> in your data. For example, <em>Klebsiella</em> produces beta-lactamase
that prevents ampicillin (or amoxicillin) from working against it. In
other words, practically every strain of <em>Klebsiella</em> is
resistant to ampicillin.</p>
<p>Sometimes, laboratory data can still contain such strains with
ampicillin being susceptible to ampicillin. This could be because an
antibiogram is available before an identification is available, and the
antibiogram is then not re-interpreted based on the identification
(namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can
be applied using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">oops</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <code class="sourceCode R"><span class="va">oops</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
<span class="st">"Escherichia"</span><span class="op">)</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
@ -226,7 +247,10 @@
<span class="co"># mo ampicillin</span> <span class="co"># mo ampicillin</span>
<span class="co"># 1 Klebsiella R</span> <span class="co"># 1 Klebsiella R</span>
<span class="co"># 2 Escherichia S</span></code></pre></div> <span class="co"># 2 Escherichia S</span></code></pre></div>
<p>A more convenient function is <code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline, but allows to check for one or more specific microorganisms or antibiotics:</p> <p>A more convenient function is
<code><a href="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code> that uses the same guideline,
but allows to check for one or more specific microorganisms or
antibiotics:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>, <code class="sourceCode R"><span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="st">"Escherichia"</span><span class="op">)</span>,
<span class="st">"ampicillin"</span><span class="op">)</span> <span class="st">"ampicillin"</span><span class="op">)</span>
@ -235,7 +259,11 @@
<span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>, <span class="fu"><a href="../reference/mo_property.html">mo_is_intrinsic_resistant</a></span><span class="op">(</span><span class="st">"Klebsiella"</span>,
<span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ampicillin"</span>, <span class="st">"kanamycin"</span><span class="op">)</span><span class="op">)</span>
<span class="co"># [1] TRUE FALSE</span></code></pre></div> <span class="co"># [1] TRUE FALSE</span></code></pre></div>
<p>EUCAST rules can not only be used for correction, they can also be used for filling in known resistance and susceptibility based on results of other antimicrobials drugs. This process is called <em>interpretive reading</em>, is basically a form of imputation, and is part of the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p> <p>EUCAST rules can not only be used for correction, they can also be
used for filling in known resistance and susceptibility based on results
of other antimicrobials drugs. This process is called <em>interpretive
reading</em>, is basically a form of imputation, and is part of the
<code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>, <code class="sourceCode R"><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>mo <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Staphylococcus aureus"</span>,
<span class="st">"Enterococcus faecalis"</span>, <span class="st">"Enterococcus faecalis"</span>,
@ -397,12 +425,14 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer> </footer>

212
docs/articles/MDR.html
View File

@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -188,7 +188,8 @@
</header><div class="row"> </header><div class="row">
<div class="col-md-9 contents"> <div class="col-md-9 contents">
<div class="page-header toc-ignore"> <div class="page-header toc-ignore">
<h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1> <h1 data-toc-skip>How to determine multi-drug resistance
(MDR)</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small> <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/MDR.Rmd" class="external-link"><code>vignettes/MDR.Rmd</code></a></small>
@ -198,54 +199,87 @@
<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which micro-organisms are multi-drug resistant organisms (MDRO).</p> <p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which
micro-organisms are multi-drug resistant organisms (MDRO).</p>
<div class="section level3"> <div class="section level3">
<h3 id="type-of-input">Type of input<a class="anchor" aria-label="anchor" href="#type-of-input"></a> <h3 id="type-of-input">Type of input<a class="anchor" aria-label="anchor" href="#type-of-input"></a>
</h3> </h3>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a regular <code>data.frame</code>. It tries to automatically determine the right columns for info about your isolates, such as the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p> <p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a
<p>For WHONET data (and most other data), all settings are automatically set correctly.</p> regular <code>data.frame</code>. It tries to automatically determine the
right columns for info about your isolates, such as the name of the
species and all columns with results of antimicrobial agents. See the
help page for more info about how to set the right settings for your
data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
<p>For WHONET data (and most other data), all settings are automatically
set correctly.</p>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="guidelines">Guidelines<a class="anchor" aria-label="anchor" href="#guidelines"></a> <h3 id="guidelines">Guidelines<a class="anchor" aria-label="anchor" href="#guidelines"></a>
</h3> </h3>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function support multiple guidelines. You can select a guideline with the <code>guideline</code> parameter. Currently supported guidelines are (case-insensitive):</p> <p>The <code><a href="../reference/mdro.html">mdro()</a></code> function support multiple guidelines. You can
select a guideline with the <code>guideline</code> parameter. Currently
supported guidelines are (case-insensitive):</p>
<ul> <ul>
<li> <li>
<p><code>guideline = "CMI2012"</code> (default)</p> <p><code>guideline = "CMI2012"</code> (default)</p>
<p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext" class="external-link">link</a>)</p> <p>Magiorakos AP, Srinivasan A <em>et al.</em> “Multidrug-resistant,
extensively drug-resistant and pandrug-resistant bacteria: an
international expert proposal for interim standard definitions for
acquired resistance.” Clinical Microbiology and Infection (2012) (<a href="https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(14)61632-3/fulltext" class="external-link">link</a>)</p>
</li> </li>
<li> <li>
<p><code>guideline = "EUCAST3.2"</code> (or simply <code>guideline = "EUCAST"</code>)</p> <p><code>guideline = "EUCAST3.2"</code> (or simply
<p>The European international guideline - EUCAST Expert Rules Version 3.2 “Intrinsic Resistance and Unusual Phenotypes” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">link</a>)</p> <code>guideline = "EUCAST"</code>)</p>
<p>The European international guideline - EUCAST Expert Rules Version
3.2 “Intrinsic Resistance and Unusual Phenotypes” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf" class="external-link">link</a>)</p>
</li> </li>
<li> <li>
<p><code>guideline = "EUCAST3.1"</code></p> <p><code>guideline = "EUCAST3.1"</code></p>
<p>The European international guideline - EUCAST Expert Rules Version 3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">link</a>)</p> <p>The European international guideline - EUCAST Expert Rules Version
3.1 “Intrinsic Resistance and Exceptional Phenotypes Tables” (<a href="https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf" class="external-link">link</a>)</p>
</li> </li>
<li> <li>
<p><code>guideline = "TB"</code></p> <p><code>guideline = "TB"</code></p>
<p>The international guideline for multi-drug resistant tuberculosis - World Health Organization “Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/" class="external-link">link</a>)</p> <p>The international guideline for multi-drug resistant tuberculosis -
World Health Organization “Companion handbook to the WHO guidelines for
the programmatic management of drug-resistant tuberculosis” (<a href="https://www.who.int/tb/publications/pmdt_companionhandbook/en/" class="external-link">link</a>)</p>
</li> </li>
<li> <li>
<p><code>guideline = "MRGN"</code></p> <p><code>guideline = "MRGN"</code></p>
<p>The German national guideline - Mueller <em>et al.</em> (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6</p> <p>The German national guideline - Mueller <em>et al.</em> (2015)
Antimicrobial Resistance and Infection Control 4:7. DOI:
10.1186/s13756-015-0047-6</p>
</li> </li>
<li> <li>
<p><code>guideline = "BRMO"</code></p> <p><code>guideline = "BRMO"</code></p>
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)” (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh" class="external-link">link</a>)</p> <p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en
Milieu “WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen)
(ZKH)” (<a href="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh" class="external-link">link</a>)</p>
</li> </li>
</ul> </ul>
<p>Please suggest your own (country-specific) guidelines by letting us know: <a href="https://github.com/msberends/AMR/issues/new" class="external-link uri">https://github.com/msberends/AMR/issues/new</a>.</p> <p>Please suggest your own (country-specific) guidelines by letting us
know: <a href="https://github.com/msberends/AMR/issues/new" class="external-link uri">https://github.com/msberends/AMR/issues/new</a>.</p>
<div class="section level4"> <div class="section level4">
<h4 id="custom-guidelines">Custom Guidelines<a class="anchor" aria-label="anchor" href="#custom-guidelines"></a> <h4 id="custom-guidelines">Custom Guidelines<a class="anchor" aria-label="anchor" href="#custom-guidelines"></a>
</h4> </h4>
<p>You can also use your own custom guideline. Custom guidelines can be set with the <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.</p> <p>You can also use your own custom guideline. Custom guidelines can be
<p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> of the <code>dplyr</code> package, you will recognise the input method to set your own rules. Rules must be set using what R considers to be the ‘formula notation’:</p> set with the <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function. This is of
great importance if you have custom rules to determine MDROs in your
hospital, e.g., rules that are dependent on ward, state of contact
isolation or other variables in your data.</p>
<p>If you are familiar with <code><a href="https://dplyr.tidyverse.org/reference/case_when.html" class="external-link">case_when()</a></code> of the
<code>dplyr</code> package, you will recognise the input method to set
your own rules. Rules must be set using what R considers to be the
‘formula notation’:</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">custom</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span><span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>, <code class="sourceCode R"><span class="va">custom</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">custom_mdro_guideline</a></span><span class="op">(</span><span class="va">CIP</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type A"</span>,
<span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span><span class="op">)</span></code></pre></div> <span class="va">ERY</span> <span class="op">==</span> <span class="st">"R"</span> <span class="op">&amp;</span> <span class="va">age</span> <span class="op">&gt;</span> <span class="fl">60</span> <span class="op">~</span> <span class="st">"Elderly Type B"</span><span class="op">)</span></code></pre></div>
<p>If a row/an isolate matches the first rule, the value after the first <code>~</code> (in this case <em>‘Elderly Type A’</em>) will be set as MDRO value. Otherwise, the second rule will be tried and so on. The maximum number of rules is unlimited.</p> <p>If a row/an isolate matches the first rule, the value after the first
<p>You can print the rules set in the console for an overview. Colours will help reading it if your console supports colours.</p> <code>~</code> (in this case <em>‘Elderly Type A’</em>) will be set as
MDRO value. Otherwise, the second rule will be tried and so on. The
maximum number of rules is unlimited.</p>
<p>You can print the rules set in the console for an overview. Colours
will help reading it if your console supports colours.</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">custom</span> <code class="sourceCode R"><span class="va">custom</span>
<span class="co"># A set of custom MDRO rules:</span> <span class="co"># A set of custom MDRO rules:</span>
@ -255,7 +289,8 @@
<span class="co"># </span> <span class="co"># </span>
<span class="co"># Unmatched rows will return NA.</span> <span class="co"># Unmatched rows will return NA.</span>
<span class="co"># Results will be of class &lt;factor&gt;, with ordered levels: Negative &lt; Elderly Type A &lt; Elderly Type B</span></code></pre></div> <span class="co"># Results will be of class &lt;factor&gt;, with ordered levels: Negative &lt; Elderly Type A &lt; Elderly Type B</span></code></pre></div>
<p>The outcome of the function can be used for the <code>guideline</code> argument in the <code><a href="../reference/mdro.html">mdro()</a></code> function:</p> <p>The outcome of the function can be used for the
<code>guideline</code> argument in the <code><a href="../reference/mdro.html">mdro()</a></code> function:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span> <code class="sourceCode R"><span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">example_isolates</span>, guideline <span class="op">=</span> <span class="va">custom</span><span class="op">)</span>
<span class="co"># Determining MDROs based on custom rules, resulting in factor levels:</span> <span class="co"># Determining MDROs based on custom rules, resulting in factor levels:</span>
@ -266,14 +301,25 @@
<span class="co"># x</span> <span class="co"># x</span>
<span class="co"># Negative Elderly Type A Elderly Type B </span> <span class="co"># Negative Elderly Type A Elderly Type B </span>
<span class="co"># 1070 198 732</span></code></pre></div> <span class="co"># 1070 198 732</span></code></pre></div>
<p>The rules set (the <code>custom</code> object in this case) could be exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">saveRDS()</a></code> if you collaborate with multiple users. The custom rules set could then be imported using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>.</p> <p>The rules set (the <code>custom</code> object in this case) could be
exported to a shared file location using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">saveRDS()</a></code> if you
collaborate with multiple users. The custom rules set could then be
imported using <code><a href="https://rdrr.io/r/base/readRDS.html" class="external-link">readRDS()</a></code>.</p>
</div> </div>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a> <h3 id="examples">Examples<a class="anchor" aria-label="anchor" href="#examples"></a>
</h3> </h3>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code> for predefined guidelines. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p> <p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains full antibiograms of 2,000 microbial isolates. It reflects reality and can be used to practise AMR data analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p> <code>factor</code> for predefined guidelines. For example, the output
of the default guideline by Magiorakos <em>et al.</em> returns a
<code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in
that order.</p>
<p>The next example uses the <code>example_isolates</code> data set.
This is a data set included with this package and contains full
antibiograms of 2,000 microbial isolates. It reflects reality and can be
used to practise AMR data analysis. If we test the MDR/XDR/PDR guideline
on this data set, we get:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># to support pipes: %&gt;%</span> <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># to support pipes: %&gt;%</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
@ -295,18 +341,34 @@
<span class="co"># Table 3 - Enterobacteriaceae... OK.</span> <span class="co"># Table 3 - Enterobacteriaceae... OK.</span>
<span class="co"># Table 4 - Pseudomonas aeruginosa... OK.</span> <span class="co"># Table 4 - Pseudomonas aeruginosa... OK.</span>
<span class="co"># Table 5 - Acinetobacter spp.... OK.</span> <span class="co"># Table 5 - Acinetobacter spp.... OK.</span>
<span class="co"># Warning: NA introduced for isolates where the available percentage of antimicrobial</span> <span class="co"># Warning: in `mdro()`: NA introduced for isolates where the available percentage of</span>
<span class="co"># classes was below 50% (set with `pct_required_classes`)</span></code></pre></div> <span class="co"># antimicrobial classes was below 50% (set with `pct_required_classes`)</span></code></pre></div>
<p>Only results with ‘R’ are considered as resistance. Use <code>combine_SI = FALSE</code> to also consider ‘I’ as resistance.</p> <p>Only results with ‘R’ are considered as resistance. Use
<p>Determining multidrug-resistant organisms (MDRO), according to: Guideline: Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Author(s): Magiorakos AP, Srinivasan A, Carey RB, …, Vatopoulos A, Weber JT, Monnet DL Source: Clinical Microbiology and Infection 18:3, 2012; doi: 10.1111/j.1469-0691.2011.03570.x</p> <code>combine_SI = FALSE</code> to also consider ‘I’ as resistance.</p>
<p>Determining multidrug-resistant organisms (MDRO), according to:
Guideline: Multidrug-resistant, extensively drug-resistant and
pandrug-resistant bacteria: an international expert proposal for interim
standard definitions for acquired resistance. Author(s): Magiorakos AP,
Srinivasan A, Carey RB, …, Vatopoulos A, Weber JT, Monnet DL Source:
Clinical Microbiology and Infection 18:3, 2012; doi:
10.1111/j.1469-0691.2011.03570.x</p>
<p>(16 isolates had no test results)</p> <p>(16 isolates had no test results)</p>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered (numeric)<br> <p>Class: factor &gt; ordered (numeric)<br>
Length: 2,000<br> Length: 2,000<br>
Levels: 4: Negative &lt; Multi-drug-resistant (MDR) &lt; Extensively drug-resistant …<br> Levels: 4: Negative &lt; Multi-drug-resistant (MDR) &lt; Extensively
drug-resistant …<br>
Available: 1,729 (86.45%, NA: 271 = 13.55%)<br> Available: 1,729 (86.45%, NA: 271 = 13.55%)<br>
Unique: 2</p> Unique: 2</p>
<table class="table"> <table style="width:100%;" class="table">
<colgroup>
<col width="4%">
<col width="38%">
<col width="9%">
<col width="12%">
<col width="16%">
<col width="19%">
</colgroup>
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
<th align="left">Item</th> <th align="left">Item</th>
@ -320,21 +382,22 @@ Unique: 2</p>
<td align="left">1</td> <td align="left">1</td>
<td align="left">Negative</td> <td align="left">Negative</td>
<td align="right">1601</td> <td align="right">1601</td>
<td align="right">92.60%</td> <td align="right">92.6%</td>
<td align="right">1601</td> <td align="right">1601</td>
<td align="right">92.60%</td> <td align="right">92.6%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">2</td> <td align="left">2</td>
<td align="left">Multi-drug-resistant (MDR)</td> <td align="left">Multi-drug-resistant (MDR)</td>
<td align="right">128</td> <td align="right">128</td>
<td align="right">7.40%</td> <td align="right">7.4%</td>
<td align="right">1729</td> <td align="right">1729</td>
<td align="right">100.00%</td> <td align="right">100.0%</td>
</tr> </tr>
</tbody> </tbody>
</table> </table>
<p>For another example, I will create a data set to determine multi-drug resistant TB:</p> <p>For another example, I will create a data set to determine multi-drug
resistant TB:</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># random_rsi() is a helper function to generate</span> <code class="sourceCode R"><span class="co"># random_rsi() is a helper function to generate</span>
<span class="co"># a random vector with values S, I and R</span> <span class="co"># a random vector with values S, I and R</span>
@ -345,7 +408,8 @@ Unique: 2</p>
pyrazinamide <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>, pyrazinamide <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
moxifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>, moxifloxacin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div> kanamycin <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span><span class="op">)</span></code></pre></div>
<p>Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same way:</p> <p>Because all column names are automatically verified for valid drug
names or codes, this would have worked exactly the same way:</p>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>, <code class="sourceCode R"><span class="va">my_TB_data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span>RIF <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
INH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>, INH <span class="op">=</span> <span class="fu"><a href="../reference/random.html">random_rsi</a></span><span class="op">(</span><span class="fl">5000</span><span class="op">)</span>,
@ -358,20 +422,21 @@ Unique: 2</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span>
<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span> <span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
<span class="co"># 1 I R I S R S</span> <span class="co"># 1 R S S I S I</span>
<span class="co"># 2 I S R R S R</span> <span class="co"># 2 R S S S R I</span>
<span class="co"># 3 R I S I R S</span> <span class="co"># 3 S S I I S S</span>
<span class="co"># 4 S S I R I S</span> <span class="co"># 4 I I S S S S</span>
<span class="co"># 5 S R S S S I</span> <span class="co"># 5 I R R I R R</span>
<span class="co"># 6 S R R S R I</span> <span class="co"># 6 I R S I S S</span>
<span class="co"># kanamycin</span> <span class="co"># kanamycin</span>
<span class="co"># 1 S</span> <span class="co"># 1 I</span>
<span class="co"># 2 I</span> <span class="co"># 2 R</span>
<span class="co"># 3 R</span> <span class="co"># 3 R</span>
<span class="co"># 4 R</span> <span class="co"># 4 S</span>
<span class="co"># 5 I</span> <span class="co"># 5 I</span>
<span class="co"># 6 R</span></code></pre></div> <span class="co"># 6 I</span></code></pre></div>
<p>We can now add the interpretation of MDR-TB to our data set. You can use:</p> <p>We can now add the interpretation of MDR-TB to our data set. You can
use:</p>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="fu"><a href="../reference/mdro.html">mdro</a></span><span class="op">(</span><span class="va">my_TB_data</span>, guideline <span class="op">=</span> <span class="st">"TB"</span><span class="op">)</span></code></pre></div>
<p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p> <p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
@ -397,10 +462,19 @@ Unique: 2</p>
<p><strong>Frequency table</strong></p> <p><strong>Frequency table</strong></p>
<p>Class: factor &gt; ordered (numeric)<br> <p>Class: factor &gt; ordered (numeric)<br>
Length: 5,000<br> Length: 5,000<br>
Levels: 5: Negative &lt; Mono-resistant &lt; Poly-resistant &lt; Multi-drug-resistant &lt;…<br> Levels: 5: Negative &lt; Mono-resistant &lt; Poly-resistant &lt;
Available: 5,000 (100.0%, NA: 0 = 0.0%)<br> Multi-drug-resistant &lt;…<br>
Available: 5,000 (100%, NA: 0 = 0%)<br>
Unique: 5</p> Unique: 5</p>
<table class="table"> <table style="width:100%;" class="table">
<colgroup>
<col width="4%">
<col width="38%">
<col width="9%">
<col width="12%">
<col width="16%">
<col width="19%">
</colgroup>
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
<th align="left">Item</th> <th align="left">Item</th>
@ -413,40 +487,40 @@ Unique: 5</p>
<tr class="odd"> <tr class="odd">
<td align="left">1</td> <td align="left">1</td>
<td align="left">Mono-resistant</td> <td align="left">Mono-resistant</td>
<td align="right">3250</td> <td align="right">3175</td>
<td align="right">65.00%</td> <td align="right">63.50%</td>
<td align="right">3250</td> <td align="right">3175</td>
<td align="right">65.00%</td> <td align="right">63.50%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">2</td> <td align="left">2</td>
<td align="left">Negative</td> <td align="left">Negative</td>
<td align="right">975</td> <td align="right">1057</td>
<td align="right">19.50%</td> <td align="right">21.14%</td>
<td align="right">4225</td> <td align="right">4232</td>
<td align="right">84.50%</td> <td align="right">84.64%</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">3</td> <td align="left">3</td>
<td align="left">Multi-drug-resistant</td> <td align="left">Multi-drug-resistant</td>
<td align="right">474</td> <td align="right">431</td>
<td align="right">9.48%</td> <td align="right">8.62%</td>
<td align="right">4699</td> <td align="right">4663</td>
<td align="right">93.98%</td> <td align="right">93.26%</td>
</tr> </tr>
<tr class="even"> <tr class="even">
<td align="left">4</td> <td align="left">4</td>
<td align="left">Poly-resistant</td> <td align="left">Poly-resistant</td>
<td align="right">203</td> <td align="right">236</td>
<td align="right">4.06%</td> <td align="right">4.72%</td>
<td align="right">4902</td> <td align="right">4899</td>
<td align="right">98.04%</td> <td align="right">97.98%</td>
</tr> </tr>
<tr class="odd"> <tr class="odd">
<td align="left">5</td> <td align="left">5</td>
<td align="left">Extensively drug-resistant</td> <td align="left">Extensively drug-resistant</td>
<td align="right">98</td> <td align="right">101</td>
<td align="right">1.96%</td> <td align="right">2.02%</td>
<td align="right">5000</td> <td align="right">5000</td>
<td align="right">100.00%</td> <td align="right">100.00%</td>
</tr> </tr>
@ -465,12 +539,14 @@ Unique: 5</p>
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<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
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<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -188,7 +188,8 @@
</header><div class="row"> </header><div class="row">
<div class="col-md-9 contents"> <div class="col-md-9 contents">
<div class="page-header toc-ignore"> <div class="page-header toc-ignore">
<h1 data-toc-skip>How to conduct principal component analysis (PCA) for AMR</h1> <h1 data-toc-skip>How to conduct principal component analysis
(PCA) for AMR</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small> <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
@ -198,17 +199,19 @@
<p><strong>NOTE: This page will be updated soon, as the pca() function is currently being developed.</strong></p> <p><strong>NOTE: This page will be updated soon, as the pca() function
<div class="section level1"> is currently being developed.</strong></p>
<h1 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> <div class="section level2">
</h1> <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
</div> </div>
<div class="section level1"> <div class="section level2">
<h1 id="transforming">Transforming<a class="anchor" aria-label="anchor" href="#transforming"></a> <h2 id="transforming">Transforming<a class="anchor" aria-label="anchor" href="#transforming"></a>
</h1> </h2>
<p>For PCA, we need to transform our AMR data first. This is what the <code>example_isolates</code> data set in this package looks like:</p> <p>For PCA, we need to transform our AMR data first. This is what the
<code>example_isolates</code> data set in this package looks like:</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR">AMR</a></span><span class="op">)</span> <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
<span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span> <span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="co"># Rows: 2,000</span> <span class="co"># Rows: 2,000</span>
@ -262,7 +265,8 @@
<span class="co"># $ COL <span style="color: #949494; font-style: italic;">&lt;rsi&gt;</span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R…</span> <span class="co"># $ COL <span style="color: #949494; font-style: italic;">&lt;rsi&gt;</span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R…</span>
<span class="co"># $ MUP <span style="color: #949494; font-style: italic;">&lt;rsi&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span> <span class="co"># $ MUP <span style="color: #949494; font-style: italic;">&lt;rsi&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span>
<span class="co"># $ RIF <span style="color: #949494; font-style: italic;">&lt;rsi&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R,…</span></code></pre></div> <span class="co"># $ RIF <span style="color: #949494; font-style: italic;">&lt;rsi&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R,…</span></code></pre></div>
<p>Now to transform this to a data set with only resistance percentages per taxonomic order and genus:</p> <p>Now to transform this to a data set with only resistance percentages
per taxonomic order and genus:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">resistance_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <code class="sourceCode R"><span class="va">resistance_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span>
@ -283,15 +287,18 @@
<span class="co"># <span style="color: #BCBCBC;">5</span> Caryophanales Gemella <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span> <span class="co"># <span style="color: #BCBCBC;">5</span> Caryophanales Gemella <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span>
<span class="co"># <span style="color: #BCBCBC;">6</span> Caryophanales Listeria <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></code></pre></div> <span class="co"># <span style="color: #BCBCBC;">6</span> Caryophanales Listeria <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></code></pre></div>
</div> </div>
<div class="section level1"> <div class="section level2">
<h1 id="perform-principal-component-analysis">Perform principal component analysis<a class="anchor" aria-label="anchor" href="#perform-principal-component-analysis"></a> <h2 id="perform-principal-component-analysis">Perform principal component analysis<a class="anchor" aria-label="anchor" href="#perform-principal-component-analysis"></a>
</h1> </h2>
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:</p> <p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows
that contain numeric values in all selected variables, so we now only
need to do:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span> <code class="sourceCode R"><span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
<span class="co"># ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span> <span class="co"># ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span>
<span class="co"># and "TOB". Total observations available: 7.</span></code></pre></div> <span class="co"># and "TOB". Total observations available: 7.</span></code></pre></div>
<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> function:</p> <p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code>
function:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span>
<span class="co"># Groups (n=4, named as 'order'):</span> <span class="co"># Groups (n=4, named as 'order'):</span>
@ -303,15 +310,21 @@
<span class="co"># Cumulative Proportion 0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></code></pre></div> <span class="co"># Cumulative Proportion 0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></code></pre></div>
<pre><code><span class="co"># Groups (n=4, named as 'order'):</span> <pre><code><span class="co"># Groups (n=4, named as 'order'):</span>
<span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span></code></pre> <span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span></code></pre>
<p>Good news. The first two components explain a total of 93.3% of the variance (see the PC1 and PC2 values of the <em>Proportion of Variance</em>. We can create a so-called biplot with the base R <code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function, to see which antimicrobial resistance per drug explain the difference per microorganism.</p> <p>Good news. The first two components explain a total of 93.3% of the
variance (see the PC1 and PC2 values of the <em>Proportion of
Variance</em>. We can create a so-called biplot with the base R
<code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function, to see which antimicrobial resistance
per drug explain the difference per microorganism.</p>
</div> </div>
<div class="section level1"> <div class="section level2">
<h1 id="plotting-the-results">Plotting the results<a class="anchor" aria-label="anchor" href="#plotting-the-results"></a> <h2 id="plotting-the-results">Plotting the results<a class="anchor" aria-label="anchor" href="#plotting-the-results"></a>
</h1> </h2>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p> <p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
<p>But we can’t see the explanation of the points. Perhaps this works better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that automatically adds the right labels and even groups:</p> <p>But we can’t see the explanation of the points. Perhaps this works
better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that
automatically adds the right labels and even groups:</p>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p> <p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p>
@ -335,12 +348,14 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -189,9 +189,10 @@
<div class="col-md-9 contents"> <div class="col-md-9 contents">
<div class="page-header toc-ignore"> <div class="page-header toc-ignore">
<h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1> <h1 data-toc-skip>How to import data from SPSS / SAS / Stata</h1>
<h4 data-toc-skip class="author">Dr. Matthijs Berends</h4> <h4 data-toc-skip class="author">Dr. Matthijs
Berends</h4>
<h4 data-toc-skip class="date">23 December 2021</h4> <h4 data-toc-skip class="date">14 March 2022</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/SPSS.Rmd" class="external-link"><code>vignettes/SPSS.Rmd</code></a></small> <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/SPSS.Rmd" class="external-link"><code>vignettes/SPSS.Rmd</code></a></small>
<div class="hidden name"><code>SPSS.Rmd</code></div> <div class="hidden name"><code>SPSS.Rmd</code></div>
@ -203,45 +204,135 @@
<div class="section level2"> <div class="section level2">
<h2 id="spss-sas-stata">SPSS / SAS / Stata<a class="anchor" aria-label="anchor" href="#spss-sas-stata"></a> <h2 id="spss-sas-stata">SPSS / SAS / Stata<a class="anchor" aria-label="anchor" href="#spss-sas-stata"></a>
</h2> </h2>
<p>SPSS (Statistical Package for the Social Sciences) is probably the most well-known software package for statistical analysis. SPSS is easier to learn than R, because in SPSS you only have to click a menu to run parts of your analysis. Because of its user-friendliness, it is taught at universities and particularly useful for students who are new to statistics. From my experience, I would guess that pretty much all (bio)medical students know it at the time they graduate. SAS and Stata are comparable statistical packages popular in big industries.</p> <p>SPSS (Statistical Package for the Social Sciences) is probably the
most well-known software package for statistical analysis. SPSS is
easier to learn than R, because in SPSS you only have to click a menu to
run parts of your analysis. Because of its user-friendliness, it is
taught at universities and particularly useful for students who are new
to statistics. From my experience, I would guess that pretty much all
(bio)medical students know it at the time they graduate. SAS and Stata
are comparable statistical packages popular in big industries.</p>
</div> </div>
<div class="section level2"> <div class="section level2">
<h2 id="compared-to-r">Compared to R<a class="anchor" aria-label="anchor" href="#compared-to-r"></a> <h2 id="compared-to-r">Compared to R<a class="anchor" aria-label="anchor" href="#compared-to-r"></a>
</h2> </h2>
<p>As said, SPSS is easier to learn than R. But SPSS, SAS and Stata come with major downsides when comparing it with R:</p> <p>As said, SPSS is easier to learn than R. But SPSS, SAS and Stata come
with major downsides when comparing it with R:</p>
<ul> <ul>
<li> <li>
<p><strong>R is highly modular.</strong></p> <p><strong>R is highly modular.</strong></p>
<p>The <a href="https://cran.r-project.org/" class="external-link">official R network (CRAN)</a> features more than 16,000 packages at the time of writing, our <code>AMR</code> package being one of them. All these packages were peer-reviewed before publication. Aside from this official channel, there are also developers who choose not to submit to CRAN, but rather keep it on their own public repository, like GitHub. So there may even be a lot more than 14,000 packages out there.</p> <p>The <a href="https://cran.r-project.org/" class="external-link">official R network
<p>Bottom line is, you can really extend it yourself or ask somebody to do this for you. Take for example our <code>AMR</code> package. Among other things, it adds reliable reference data to R to help you with the data cleaning and analysis. SPSS, SAS and Stata will never know what a valid MIC value is or what the Gram stain of <em>E. coli</em> is. Or that all species of <em>Klebiella</em> are resistant to amoxicillin and that Floxapen<sup>®</sup> is a trade name of flucloxacillin. These facts and properties are often needed to clean existing data, which would be very inconvenient in a software package without reliable reference data. See below for a demonstration.</p> (CRAN)</a> features more than 16,000 packages at the time of writing,
our <code>AMR</code> package being one of them. All these packages were
peer-reviewed before publication. Aside from this official channel,
there are also developers who choose not to submit to CRAN, but rather
keep it on their own public repository, like GitHub. So there may even
be a lot more than 14,000 packages out there.</p>
<p>Bottom line is, you can really extend it yourself or ask somebody to
do this for you. Take for example our <code>AMR</code> package. Among
other things, it adds reliable reference data to R to help you with the
data cleaning and analysis. SPSS, SAS and Stata will never know what a
valid MIC value is or what the Gram stain of <em>E. coli</em> is. Or
that all species of <em>Klebiella</em> are resistant to amoxicillin and
that Floxapen<sup>®</sup> is a trade name of flucloxacillin. These facts
and properties are often needed to clean existing data, which would be
very inconvenient in a software package without reliable reference data.
See below for a demonstration.</p>
</li> </li>
<li> <li>
<p><strong>R is extremely flexible.</strong></p> <p><strong>R is extremely flexible.</strong></p>
<p>Because you write the syntax yourself, you can do anything you want. The flexibility in transforming, arranging, grouping and summarising data, or drawing plots, is endless - with SPSS, SAS or Stata you are bound to their algorithms and format styles. They may be a bit flexible, but you can probably never create that very specific publication-ready plot without using other (paid) software. If you sometimes write syntaxes in SPSS to run a complete analysis or to ‘automate’ some of your work, you could do this a lot less time in R. You will notice that writing syntaxes in R is a lot more nifty and clever than in SPSS. Still, as working with any statistical package, you will have to have knowledge about what you are doing (statistically) and what you are willing to accomplish.</p> <p>Because you write the syntax yourself, you can do anything you want.
The flexibility in transforming, arranging, grouping and summarising
data, or drawing plots, is endless - with SPSS, SAS or Stata you are
bound to their algorithms and format styles. They may be a bit flexible,
but you can probably never create that very specific publication-ready
plot without using other (paid) software. If you sometimes write
syntaxes in SPSS to run a complete analysis or to ‘automate’ some of
your work, you could do this a lot less time in R. You will notice that
writing syntaxes in R is a lot more nifty and clever than in SPSS.
Still, as working with any statistical package, you will have to have
knowledge about what you are doing (statistically) and what you are
willing to accomplish.</p>
</li> </li>
<li> <li>
<p><strong>R can be easily automated.</strong></p> <p><strong>R can be easily automated.</strong></p>
<p>Over the last years, <a href="https://rmarkdown.rstudio.com/" class="external-link">R Markdown</a> has really made an interesting development. With R Markdown, you can very easily produce reports, whether the format has to be Word, PowerPoint, a website, a PDF document or just the raw data to Excel. It even allows the use of a reference file containing the layout style (e.g. fonts and colours) of your organisation. I use this a lot to generate weekly and monthly reports automatically. Just write the code once and enjoy the automatically updated reports at any interval you like.</p> <p>Over the last years, <a href="https://rmarkdown.rstudio.com/" class="external-link">R
<p>For an even more professional environment, you could create <a href="https://shiny.rstudio.com/" class="external-link">Shiny apps</a>: live manipulation of data using a custom made website. The webdesign knowledge needed (JavaScript, CSS, HTML) is almost <em>zero</em>.</p> Markdown</a> has really made an interesting development. With R
Markdown, you can very easily produce reports, whether the format has to
be Word, PowerPoint, a website, a PDF document or just the raw data to
Excel. It even allows the use of a reference file containing the layout
style (e.g. fonts and colours) of your organisation. I use this a lot to
generate weekly and monthly reports automatically. Just write the code
once and enjoy the automatically updated reports at any interval you
like.</p>
<p>For an even more professional environment, you could create <a href="https://shiny.rstudio.com/" class="external-link">Shiny apps</a>: live manipulation of
data using a custom made website. The webdesign knowledge needed
(JavaScript, CSS, HTML) is almost <em>zero</em>.</p>
</li> </li>
<li> <li>
<p><strong>R has a huge community.</strong></p> <p><strong>R has a huge community.</strong></p>
<p>Many R users just ask questions on websites like <a href="https://stackoverflow.com" class="external-link">StackOverflow.com</a>, the largest online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes" class="external-link">430,288 R-related questions</a> have already been asked on this platform (that covers questions and answers for any programming language). In my own experience, most questions are answered within a couple of minutes.</p> <p>Many R users just ask questions on websites like <a href="https://stackoverflow.com" class="external-link">StackOverflow.com</a>, the largest
online community for programmers. At the time of writing, <a href="https://stackoverflow.com/questions/tagged/r?sort=votes" class="external-link">439,954
R-related questions</a> have already been asked on this platform (that
covers questions and answers for any programming language). In my own
experience, most questions are answered within a couple of
minutes.</p>
</li> </li>
<li> <li>
<p><strong>R understands any data type, including SPSS/SAS/Stata.</strong></p> <p><strong>R understands any data type, including
<p>And that’s not vice versa I’m afraid. You can import data from any source into R. For example from SPSS, SAS and Stata (<a href="https://haven.tidyverse.org/" class="external-link">link</a>), from Minitab, Epi Info and EpiData (<a href="https://cran.r-project.org/package=foreign" class="external-link">link</a>), from Excel (<a href="https://readxl.tidyverse.org/" class="external-link">link</a>), from flat files like CSV, TXT or TSV (<a href="https://readr.tidyverse.org/" class="external-link">link</a>), or directly from databases and datawarehouses from anywhere on the world (<a href="https://dbplyr.tidyverse.org/" class="external-link">link</a>). You can even scrape websites to download tables that are live on the internet (<a href="https://github.com/hadley/rvest" class="external-link">link</a>) or get the results of an API call and transform it into data in only one command (<a href="https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread" class="external-link">link</a>).</p> SPSS/SAS/Stata.</strong></p>
<p>And the best part - you can export from R to most data formats as well. So you can import an SPSS file, do your analysis neatly in R and export the resulting tables to Excel files for sharing.</p> <p>And that’s not vice versa I’m afraid. You can import data from any
source into R. For example from SPSS, SAS and Stata (<a href="https://haven.tidyverse.org/" class="external-link">link</a>), from Minitab, Epi Info
and EpiData (<a href="https://cran.r-project.org/package=foreign" class="external-link">link</a>), from Excel
(<a href="https://readxl.tidyverse.org/" class="external-link">link</a>), from flat files like
CSV, TXT or TSV (<a href="https://readr.tidyverse.org/" class="external-link">link</a>), or
directly from databases and datawarehouses from anywhere on the world
(<a href="https://dbplyr.tidyverse.org/" class="external-link">link</a>). You can even scrape
websites to download tables that are live on the internet (<a href="https://github.com/hadley/rvest" class="external-link">link</a>) or get the results of
an API call and transform it into data in only one command (<a href="https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread" class="external-link">link</a>).</p>
<p>And the best part - you can export from R to most data formats as
well. So you can import an SPSS file, do your analysis neatly in R and
export the resulting tables to Excel files for sharing.</p>
</li> </li>
<li> <li>
<p><strong>R is completely free and open-source.</strong></p> <p><strong>R is completely free and open-source.</strong></p>
<p>No strings attached. It was created and is being maintained by volunteers who believe that (data) science should be open and publicly available to everybody. SPSS, SAS and Stata are quite expensive. IBM SPSS Staticstics only comes with subscriptions nowadays, varying <a href="https://www.ibm.com/products/spss-statistics/pricing" class="external-link">between USD 1,300 and USD 8,500</a> per user <em>per year</em>. SAS Analytics Pro costs <a href="https://www.sas.com/store/products-solutions/sas-analytics-pro/prodPERSANL.html" class="external-link">around USD 10,000</a> per computer. Stata also has a business model with subscription fees, varying <a href="https://www.stata.com/order/new/bus/single-user-licenses/dl/" class="external-link">between USD 600 and USD 2,800</a> per computer per year, but lower prices come with a limitation of the number of variables you can work with. And still they do not offer the above benefits of R.</p> <p>No strings attached. It was created and is being maintained by
<p>If you are working at a midsized or small company, you can save it tens of thousands of dollars by using R instead of e.g. SPSS - gaining even more functions and flexibility. And all R enthousiasts can do as much PR as they want (like I do here), because nobody is officially associated with or affiliated by R. It is really free.</p> volunteers who believe that (data) science should be open and publicly
available to everybody. SPSS, SAS and Stata are quite expensive. IBM
SPSS Staticstics only comes with subscriptions nowadays, varying <a href="https://www.ibm.com/products/spss-statistics/pricing" class="external-link">between USD
1,300 and USD 8,500</a> per user <em>per year</em>. SAS Analytics Pro
costs <a href="https://www.sas.com/store/products-solutions/sas-analytics-pro/prodPERSANL.html" class="external-link">around
USD 10,000</a> per computer. Stata also has a business model with
subscription fees, varying <a href="https://www.stata.com/order/new/bus/single-user-licenses/dl/" class="external-link">between
USD 600 and USD 2,800</a> per computer per year, but lower prices come
with a limitation of the number of variables you can work with. And
still they do not offer the above benefits of R.</p>
<p>If you are working at a midsized or small company, you can save it
tens of thousands of dollars by using R instead of e.g. SPSS - gaining
even more functions and flexibility. And all R enthousiasts can do as
much PR as they want (like I do here), because nobody is officially
associated with or affiliated by R. It is really free.</p>
</li> </li>
<li> <li>
<p><strong>R is (nowadays) the preferred analysis software in academic papers.</strong></p> <p><strong>R is (nowadays) the preferred analysis software in
<p>At present, R is among the world most powerful statistical languages, and it is generally very popular in science (Bollmann <em>et al.</em>, 2017). For all the above reasons, the number of references to R as an analysis method in academic papers <a href="https://r4stats.com/2014/08/20/r-passes-spss-in-scholarly-use-stata-growing-rapidly/" class="external-link">is rising continuously</a> and has even surpassed SPSS for academic use (Muenchen, 2014).</p> academic papers.</strong></p>
<p>I believe that the thing with SPSS is, that it has always had a great user interface which is very easy to learn and use. Back when they developed it, they had very little competition, let alone from R. R didn’t even had a professional user interface until the last decade (called RStudio, see below). How people used R between the nineties and 2010 is almost completely incomparable to how R is being used now. The language itself <a href="https://www.tidyverse.org/packages/" class="external-link">has been restyled completely</a> by volunteers who are dedicated professionals in the field of data science. SPSS was great when there was nothing else that could compete. But now in 2021, I don’t see any reason why SPSS would be of any better use than R.</p> <p>At present, R is among the world most powerful statistical languages,
and it is generally very popular in science (Bollmann <em>et al.</em>,
2017). For all the above reasons, the number of references to R as an
analysis method in academic papers <a href="https://r4stats.com/2014/08/20/r-passes-spss-in-scholarly-use-stata-growing-rapidly/" class="external-link">is
rising continuously</a> and has even surpassed SPSS for academic use
(Muenchen, 2014).</p>
<p>I believe that the thing with SPSS is, that it has always had a great
user interface which is very easy to learn and use. Back when they
developed it, they had very little competition, let alone from R. R
didn’t even had a professional user interface until the last decade
(called RStudio, see below). How people used R between the nineties and
2010 is almost completely incomparable to how R is being used now. The
language itself <a href="https://www.tidyverse.org/packages/" class="external-link">has been
restyled completely</a> by volunteers who are dedicated professionals in
the field of data science. SPSS was great when there was nothing else
that could compete. But now in 2022, I don’t see any reason why SPSS
would be of any better use than R.</p>
</li> </li>
</ul> </ul>
<p>To demonstrate the first point:</p> <p>To demonstrate the first point:</p>
@ -285,13 +376,23 @@
<div class="section level3"> <div class="section level3">
<h3 id="rstudio">RStudio<a class="anchor" aria-label="anchor" href="#rstudio"></a> <h3 id="rstudio">RStudio<a class="anchor" aria-label="anchor" href="#rstudio"></a>
</h3> </h3>
<p>To work with R, probably the best option is to use <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio</a>. It is an open-source and free desktop environment which not only allows you to run R code, but also supports project management, version management, package management and convenient import menus to work with other data sources. You can also install <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio Server</a> on a private or corporate server, which brings nothing less than the complete RStudio software to you as a website (at home or at work).</p> <p>To work with R, probably the best option is to use <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio</a>. It is an
<p>To import a data file, just click <em>Import Dataset</em> in the Environment tab:</p> open-source and free desktop environment which not only allows you to
run R code, but also supports project management, version management,
package management and convenient import menus to work with other data
sources. You can also install <a href="https://www.rstudio.com/products/rstudio/" class="external-link">RStudio Server</a> on a
private or corporate server, which brings nothing less than the complete
RStudio software to you as a website (at home or at work).</p>
<p>To import a data file, just click <em>Import Dataset</em> in the
Environment tab:</p>
<p><img src="https://github.com/msberends/AMR/raw/main/docs/import1.png"></p> <p><img src="https://github.com/msberends/AMR/raw/main/docs/import1.png"></p>
<p>If additional packages are needed, RStudio will ask you if they should be installed on beforehand.</p> <p>If additional packages are needed, RStudio will ask you if they
<p>In the the window that opens, you can define all options (parameters) that should be used for import and you’re ready to go:</p> should be installed on beforehand.</p>
<p>In the the window that opens, you can define all options (parameters)
that should be used for import and you’re ready to go:</p>
<p><img src="https://github.com/msberends/AMR/raw/main/docs/import2.png"></p> <p><img src="https://github.com/msberends/AMR/raw/main/docs/import2.png"></p>
<p>If you want named variables to be imported as factors so it resembles SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html" class="external-link">as_factor()</a></code>.</p> <p>If you want named variables to be imported as factors so it resembles
SPSS more, use <code><a href="https://haven.tidyverse.org/reference/as_factor.html" class="external-link">as_factor()</a></code>.</p>
<p>The difference is this:</p> <p>The difference is this:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">SPSS_data</span> <code class="sourceCode R"><span class="va">SPSS_data</span>
@ -329,7 +430,8 @@
<div class="section level3"> <div class="section level3">
<h3 id="base-r">Base R<a class="anchor" aria-label="anchor" href="#base-r"></a> <h3 id="base-r">Base R<a class="anchor" aria-label="anchor" href="#base-r"></a>
</h3> </h3>
<p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/" class="external-link">great <code>haven</code> package</a> yourself:</p> <p>To import data from SPSS, SAS or Stata, you can use the <a href="https://haven.tidyverse.org/" class="external-link">great <code>haven</code> package</a>
yourself:</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># download and install the latest version:</span> <code class="sourceCode R"><span class="co"># download and install the latest version:</span>
<span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"haven"</span><span class="op">)</span>
@ -409,12 +511,14 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer> </footer>

58
docs/articles/WHONET.html
View File

@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -201,26 +201,43 @@
<div class="section level3"> <div class="section level3">
<h3 id="import-of-data">Import of data<a class="anchor" aria-label="anchor" href="#import-of-data"></a> <h3 id="import-of-data">Import of data<a class="anchor" aria-label="anchor" href="#import-of-data"></a>
</h3> </h3>
<p>This tutorial assumes you already imported the WHONET data with e.g. the <a href="https://readxl.tidyverse.org/" class="external-link"><code>readxl</code> package</a>. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.</p> <p>This tutorial assumes you already imported the WHONET data with
e.g. the <a href="https://readxl.tidyverse.org/" class="external-link"><code>readxl</code>
package</a>. In RStudio, this can be done using the menu button ‘Import
Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and
select your exported file. Make sure date fields are imported
correctly.</p>
<p>An example syntax could look like this:</p> <p>An example syntax could look like this:</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org" class="external-link">readxl</a></span><span class="op">)</span> <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://readxl.tidyverse.org" class="external-link">readxl</a></span><span class="op">)</span>
<span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html" class="external-link">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></code></pre></div> <span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://readxl.tidyverse.org/reference/read_excel.html" class="external-link">read_excel</a></span><span class="op">(</span>path <span class="op">=</span> <span class="st">"path/to/your/file.xlsx"</span><span class="op">)</span></code></pre></div>
<p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example data set <code>WHONET</code></a>. We will use it for this analysis.</p> <p>This package comes with an <a href="https://msberends.github.io/AMR/reference/WHONET.html">example
data set <code>WHONET</code></a>. We will use it for this analysis.</p>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="preparation">Preparation<a class="anchor" aria-label="anchor" href="#preparation"></a> <h3 id="preparation">Preparation<a class="anchor" aria-label="anchor" href="#preparation"></a>
</h3> </h3>
<p>First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="external-link uri">https://www.tidyverse.org/</a>.</p> <p>First, load the relevant packages if you did not yet did this. I use
the tidyverse for all of my analyses. All of them. If you don’t know it
yet, I suggest you read about it on their website: <a href="https://www.tidyverse.org/" class="external-link uri">https://www.tidyverse.org/</a>.</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span> <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span> <span class="co"># part of tidyverse</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR">AMR</a></span><span class="op">)</span> <span class="co"># this package</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span> <span class="co"># this package</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/msberends/cleaner" class="external-link">cleaner</a></span><span class="op">)</span> <span class="co"># to create frequency tables</span></code></pre></div>
<p>We will have to transform some variables to simplify and automate the analysis:</p> <p>We will have to transform some variables to simplify and automate the
analysis:</p>
<ul> <ul>
<li>Microorganisms should be transformed to our own microorganism codes (called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our Catalogue of Life reference data set</a>, which contains all ~70,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also recognises almost all WHONET abbreviations of microorganisms.</li> <li>Microorganisms should be transformed to our own microorganism codes
<li>Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values <code>"S"</code>, <code>"I"</code> or <code>"R"</code>. That is exactly where the <code><a href="../reference/as.rsi.html">as.rsi()</a></code> function is for.</li> (called an <code>mo</code>) using <a href="https://msberends.github.io/AMR/reference/catalogue_of_life">our
Catalogue of Life reference data set</a>, which contains all ~70,000
microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa.
We do the tranformation with <code><a href="../reference/as.mo.html">as.mo()</a></code>. This function also
recognises almost all WHONET abbreviations of microorganisms.</li>
<li>Antimicrobial results or interpretations have to be clean and valid.
In other words, they should only contain values <code>"S"</code>,
<code>"I"</code> or <code>"R"</code>. That is exactly where the
<code><a href="../reference/as.rsi.html">as.rsi()</a></code> function is for.</li>
</ul> </ul>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># transform variables</span> <code class="sourceCode R"><span class="co"># transform variables</span>
@ -230,7 +247,9 @@
<span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span> <span class="co"># transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></code></pre></div> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMP_ND10</span><span class="op">:</span><span class="va">CIP_EE</span><span class="op">)</span>, <span class="va">as.rsi</span><span class="op">)</span></code></pre></div>
<p>No errors or warnings, so all values are transformed succesfully.</p> <p>No errors or warnings, so all values are transformed succesfully.</p>
<p>We also created a package dedicated to data cleaning and checking, called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code> function can be used to create frequency tables.</p> <p>We also created a package dedicated to data cleaning and checking,
called the <code>cleaner</code> package. Its <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html" class="external-link">freq()</a></code>
function can be used to create frequency tables.</p>
<p>So let’s check our data, with a couple of frequency tables:</p> <p>So let’s check our data, with a couple of frequency tables:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># our newly created `mo` variable, put in the mo_name() function</span> <code class="sourceCode R"><span class="co"># our newly created `mo` variable, put in the mo_name() function</span>
@ -238,11 +257,19 @@
<p><strong>Frequency table</strong></p> <p><strong>Frequency table</strong></p>
<p>Class: character<br> <p>Class: character<br>
Length: 500<br> Length: 500<br>
Available: 500 (100.0%, NA: 0 = 0.0%)<br> Available: 500 (100%, NA: 0 = 0%)<br>
Unique: 37</p> Unique: 37</p>
<p>Shortest: 11<br> <p>Shortest: 11<br>
Longest: 40</p> Longest: 40</p>
<table class="table"> <table class="table">
<colgroup>
<col width="4%">
<col width="47%">
<col width="7%">
<col width="10%">
<col width="13%">
<col width="15%">
</colgroup>
<thead><tr class="header"> <thead><tr class="header">
<th align="left"></th> <th align="left"></th>
<th align="left">Item</th> <th align="left">Item</th>
@ -334,7 +361,7 @@ Longest: 40</p>
</tr> </tr>
</tbody> </tbody>
</table> </table>
<p>(omitted 27 entries, n = 56 [11.20%])</p> <p>(omitted 27 entries, n = 56 [11.2%])</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># our transformed antibiotic columns</span> <code class="sourceCode R"><span class="co"># our transformed antibiotic columns</span>
<span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span> <span class="co"># amoxicillin/clavulanic acid (J01CR02) as an example</span>
@ -388,7 +415,8 @@ Drug group: Beta-lactams/penicillins<br>
<div class="section level3"> <div class="section level3">
<h3 id="a-first-glimpse-at-results">A first glimpse at results<a class="anchor" aria-label="anchor" href="#a-first-glimpse-at-results"></a> <h3 id="a-first-glimpse-at-results">A first glimpse at results<a class="anchor" aria-label="anchor" href="#a-first-glimpse-at-results"></a>
</h3> </h3>
<p>An easy <code>ggplot</code> will already give a lot of information, using the included <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function:</p> <p>An easy <code>ggplot</code> will already give a lot of information,
using the included <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> function:</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <code class="sourceCode R"><span class="va">data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">Country</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
@ -408,12 +436,14 @@ Drug group: Beta-lactams/penicillins<br>
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer> </footer>

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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -198,14 +198,30 @@
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (CoL) and the <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (LPSN). We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the microbial taxonomy.</p> <p>One of the most important features of this package is the complete
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p> microbial taxonomic database, supplied by the <a href="http://www.catalogueoflife.org" class="external-link">Catalogue of Life</a> (CoL) and
the <a href="https://lpsn.dsmz.de" class="external-link">List of Prokaryotic names with
Standing in Nomenclature</a> (LPSN). We created a function
<code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid
microbial ID by using intelligent rules combined with the microbial
taxonomy.</p>
<p>Using the <code>microbenchmark</code> package, we can review the
calculation performance of this function. Its function
<code><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark()</a></code> runs different input expressions
independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/" class="external-link">microbenchmark</a></span><span class="op">)</span> <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/joshuaulrich/microbenchmark/" class="external-link">microbenchmark</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR">AMR</a></span><span class="op">)</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></code></pre></div> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></code></pre></div>
<p>In the next test, we try to ‘coerce’ different input values into the microbial code of <em>Staphylococcus aureus</em>. Coercion is a computational process of forcing output based on an input. For microorganism names, coercing user input to taxonomically valid microorganism names is crucial to ensure correct interpretation and to enable grouping based on taxonomic properties.</p> <p>In the next test, we try to ‘coerce’ different input values into the
<p>The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, its taxonomic kingdom).</p> microbial code of <em>Staphylococcus aureus</em>. Coercion is a
computational process of forcing output based on an input. For
microorganism names, coercing user input to taxonomically valid
microorganism names is crucial to ensure correct interpretation and to
enable grouping based on taxonomic properties.</p>
<p>The actual result is the same every time: it returns its
microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for
<em>Bacteria</em>, its taxonomic kingdom).</p>
<p>But the calculation time differs a lot:</p> <p>But the calculation time differs a lot:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span> <code class="sourceCode R"><span class="va">S.aureus</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>
@ -224,27 +240,40 @@
times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span> times <span class="op">=</span> <span class="fl">25</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span> <span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">S.aureus</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span> <span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span> <span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># as.mo("sau") 10.0 12.0 20.0 12.0 15.0 53 25</span> <span class="co"># as.mo("sau") 12.0 13 18.0 14.0 15.0 48 25</span>
<span class="co"># as.mo("stau") 49.0 54.0 72.0 58.0 91.0 97 25</span> <span class="co"># as.mo("stau") 54.0 59 80.0 91.0 96.0 99 25</span>
<span class="co"># as.mo("STAU") 50.0 54.0 71.0 57.0 90.0 110 25</span> <span class="co"># as.mo("STAU") 53.0 61 77.0 66.0 94.0 100 25</span>
<span class="co"># as.mo("staaur") 10.0 12.0 17.0 12.0 14.0 51 25</span> <span class="co"># as.mo("staaur") 12.0 13 19.0 14.0 16.0 62 25</span>
<span class="co"># as.mo("STAAUR") 10.0 12.0 17.0 12.0 14.0 54 25</span> <span class="co"># as.mo("STAAUR") 12.0 13 16.0 14.0 15.0 48 25</span>
<span class="co"># as.mo("S. aureus") 26.0 27.0 40.0 31.0 56.0 74 25</span> <span class="co"># as.mo("S. aureus") 28.0 30 38.0 33.0 35.0 69 25</span>
<span class="co"># as.mo("S aureus") 26.0 27.0 39.0 29.0 58.0 68 25</span> <span class="co"># as.mo("S aureus") 27.0 31 46.0 34.0 65.0 73 25</span>
<span class="co"># as.mo("Staphylococcus aureus") 3.5 3.9 6.6 4.1 4.8 38 25</span> <span class="co"># as.mo("Staphylococcus aureus") 3.7 4 6.7 4.3 4.5 36 25</span>
<span class="co"># as.mo("Staphylococcus aureus (MRSA)") 230.0 240.0 250.0 240.0 250.0 280 25</span> <span class="co"># as.mo("Staphylococcus aureus (MRSA)") 260.0 270 290.0 280.0 290.0 360 25</span>
<span class="co"># as.mo("Sthafilokkockus aaureuz") 180.0 190.0 200.0 190.0 200.0 290 25</span> <span class="co"># as.mo("Sthafilokkockus aaureuz") 190.0 210 220.0 210.0 220.0 330 25</span>
<span class="co"># as.mo("MRSA") 11.0 12.0 19.0 13.0 14.0 50 25</span> <span class="co"># as.mo("MRSA") 12.0 13 20.0 14.0 16.0 68 25</span>
<span class="co"># as.mo("VISA") 21.0 22.0 32.0 25.0 50.0 60 25</span></code></pre></div> <span class="co"># as.mo("VISA") 22.0 23 32.0 25.0 27.0 63 25</span></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></p> <p><img src="benchmarks_files/figure-html/unnamed-chunk-4-1.png" width="750"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 200 milliseconds, this is only 5 input values per second. It is clear that accepted taxonomic names are extremely fast, but some variations are up to 47 times slower to determine.</p> <p>In the table above, all measurements are shown in milliseconds
<p>To improve performance, we implemented two important algorithms to save unnecessary calculations: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p> (thousands of seconds). A value of 5 milliseconds means it can determine
200 input values per second. It case of 200 milliseconds, this is only 5
input values per second. It is clear that accepted taxonomic names are
extremely fast, but some variations are up to 67 times slower to
determine.</p>
<p>To improve performance, we implemented two important algorithms to
save unnecessary calculations: <strong>repetitive results</strong> and
<strong>already precalculated results</strong>.</p>
<div class="section level3"> <div class="section level3">
<h3 id="repetitive-results">Repetitive results<a class="anchor" aria-label="anchor" href="#repetitive-results"></a> <h3 id="repetitive-results">Repetitive results<a class="anchor" aria-label="anchor" href="#repetitive-results"></a>
</h3> </h3>
<p>Repetitive results are values that are present more than once in a vector. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. So running <code>as.mo(c("E. coli", "E. coli"))</code> will check the value <code>"E. coli"</code> only once.</p> <p>Repetitive results are values that are present more than once in a
<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p> vector. Unique values will only be calculated once by
<code><a href="../reference/as.mo.html">as.mo()</a></code>. So running
<code>as.mo(c("E. coli", "E. coli"))</code> will check the value
<code>"E. coli"</code> only once.</p>
<p>To prove this, we will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for testing - a
helper function that returns the full microbial name (genus, species and
possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="co"># start with the example_isolates data set</span> <code class="sourceCode R"><span class="co"># start with the example_isolates data set</span>
<span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="va">x</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
@ -258,8 +287,8 @@
<span class="co"># what do these values look like? They are of class &lt;mo&gt;:</span> <span class="co"># what do these values look like? They are of class &lt;mo&gt;:</span>
<span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
<span class="co"># Class &lt;mo&gt;</span> <span class="co"># Class &lt;mo&gt;</span>
<span class="co"># [1] B_STPHY_AURS B_STRPT_EQNS B_KLBSL_PNMN B_STPHY_EPDR B_STPHY_AURS</span> <span class="co"># [1] B_ESCHR_COLI B_STRPT_MITS B_STRPT_ANGN B_STPHY_CONS B_ESCHR_COLI</span>
<span class="co"># [6] B_CRYNB_STRT</span> <span class="co"># [6] B_ESCHR_COLI</span>
<span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span> <span class="co"># as the example_isolates data set has 2,000 rows, we should have 2 million items</span>
<span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>
@ -275,13 +304,20 @@
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span> <span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span> <span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span> <span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># mo_name(x) 196 209 274 223 364 388 10</span></code></pre></div> <span class="co"># mo_name(x) 207 225 288 233 370 414 10</span></code></pre></div>
<p>So getting official taxonomic names of 2,000,000 (!!) items consisting of 90 unique values only takes 0.223 seconds. That is 112 nanoseconds on average. You only lose time on your unique input values.</p> <p>So getting official taxonomic names of 2,000,000 (!!) items
consisting of 90 unique values only takes 0.233 seconds. That is 117
nanoseconds on average. You only lose time on your unique input
values.</p>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="precalculated-results">Precalculated results<a class="anchor" aria-label="anchor" href="#precalculated-results"></a> <h3 id="precalculated-results">Precalculated results<a class="anchor" aria-label="anchor" href="#precalculated-results"></a>
</h3> </h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function such as <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all. In other words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it will return the results immediately (see ‘C’ below):</p> <p>What about precalculated results? If the input is an already
precalculated result of a helper function such as
<code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all. In other
words, if you run <code><a href="../reference/mo_property.html">mo_name()</a></code> on a valid taxonomic name, it
will return the results immediately (see ‘C’ below):</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>, <code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"STAAUR"</span><span class="op">)</span>,
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>, B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="st">"S. aureus"</span><span class="op">)</span>,
@ -289,11 +325,14 @@
times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span> times <span class="op">=</span> <span class="fl">10</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span> <span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span> <span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span> <span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 8.00 9.16 9.19 9.28 9.46 9.73 10</span> <span class="co"># A 10.3 10.90 11.20 11.10 11.20 12.40 10</span>
<span class="co"># B 23.40 27.20 32.60 27.90 28.10 80.20 10</span> <span class="co"># B 31.3 32.70 38.20 33.90 35.20 79.80 10</span>
<span class="co"># C 1.85 2.25 2.40 2.47 2.62 2.90 10</span></code></pre></div> <span class="co"># C 2.5 2.64 2.79 2.78 2.85 3.13 10</span></code></pre></div>
<p>So going from <code>mo_name("Staphylococcus aureus")</code> to <code>"Staphylococcus aureus"</code> takes 0.0025 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p> <p>So going from <code>mo_name("Staphylococcus aureus")</code> to
<code>"Staphylococcus aureus"</code> takes 0.0028 seconds - it doesn’t
even start calculating <em>if the result would be the same as the
expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>, <code class="sourceCode R"><span class="va">run_it</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html" class="external-link">microbenchmark</a></span><span class="op">(</span>A <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"aureus"</span><span class="op">)</span>,
B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>, B <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"Staphylococcus"</span><span class="op">)</span>,
@ -307,20 +346,28 @@
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span> <span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span> <span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span> <span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># A 1.76 1.80 2.07 1.95 2.26 2.90 10</span> <span class="co"># A 2.30 2.55 2.68 2.66 2.85 2.94 10</span>
<span class="co"># B 1.69 1.73 1.90 1.81 2.03 2.48 10</span> <span class="co"># B 2.27 2.38 2.59 2.56 2.83 2.88 10</span>
<span class="co"># C 1.71 1.77 1.92 1.91 2.05 2.17 10</span> <span class="co"># C 2.22 2.25 2.51 2.47 2.74 2.87 10</span>
<span class="co"># D 1.68 1.71 1.76 1.76 1.82 1.88 10</span> <span class="co"># D 2.21 2.40 2.68 2.73 2.94 3.08 10</span>
<span class="co"># E 1.68 1.70 1.89 1.89 2.04 2.26 10</span> <span class="co"># E 2.22 2.28 2.46 2.45 2.56 2.81 10</span>
<span class="co"># F 1.67 1.75 1.93 1.89 2.11 2.35 10</span> <span class="co"># F 2.19 2.34 2.52 2.48 2.71 3.04 10</span>
<span class="co"># G 1.70 1.76 1.97 1.88 2.12 2.43 10</span> <span class="co"># G 2.23 2.40 2.52 2.46 2.62 2.88 10</span>
<span class="co"># H 1.67 1.71 1.83 1.75 1.98 2.14 10</span></code></pre></div> <span class="co"># H 2.13 2.25 2.42 2.47 2.50 2.77 10</span></code></pre></div>
<p>Of course, when running <code>mo_phylum("Firmicutes")</code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> anyway, there is no point in calculating the result. And because this package contains all phyla of all known bacteria, it can just return the initial value immediately.</p> <p>Of course, when running <code>mo_phylum("Firmicutes")</code> the
function has zero knowledge about the actual microorganism, namely
<em>S. aureus</em>. But since the result would be
<code>"Firmicutes"</code> anyway, there is no point in calculating the
result. And because this package contains all phyla of all known
bacteria, it can just return the initial value immediately.</p>
</div> </div>
<div class="section level3"> <div class="section level3">
<h3 id="results-in-other-languages">Results in other languages<a class="anchor" aria-label="anchor" href="#results-in-other-languages"></a> <h3 id="results-in-other-languages">Results in other languages<a class="anchor" aria-label="anchor" href="#results-in-other-languages"></a>
</h3> </h3>
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time (compare “en” from the table below with the other languages):</p> <p>When the system language is non-English and supported by this
<code>AMR</code> package, some functions will have a translated result.
This almost does’t take extra time (compare “en” from the table below
with the other languages):</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">CoNS</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"CoNS"</span><span class="op">)</span> <code class="sourceCode R"><span class="va">CoNS</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"CoNS"</span><span class="op">)</span>
<span class="va">CoNS</span> <span class="va">CoNS</span>
@ -349,18 +396,19 @@
times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span> times <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>
<span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span> <span class="fu"><a href="https://docs.ropensci.org/skimr/reference/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">run_it</span>, unit <span class="op">=</span> <span class="st">"ms"</span>, signif <span class="op">=</span> <span class="fl">4</span><span class="op">)</span>
<span class="co"># Unit: milliseconds</span> <span class="co"># Unit: milliseconds</span>
<span class="co"># expr min lq mean median uq max neval</span> <span class="co"># expr min lq mean median uq max neval</span>
<span class="co"># da 1.9470 2.0220 2.190 2.0720 2.358 3.234 100</span> <span class="co"># da 2.1730 2.476 3.956 2.609 2.873 45.180 100</span>
<span class="co"># de 1.9560 2.0330 3.649 2.1610 2.401 50.670 100</span> <span class="co"># de 2.2170 2.497 3.161 2.646 2.855 48.260 100</span>
<span class="co"># en 0.8937 0.9124 1.022 0.9776 1.120 1.748 100</span> <span class="co"># en 0.9509 1.122 1.640 1.183 1.321 38.430 100</span>
<span class="co"># es 1.9710 2.0290 2.216 2.1000 2.391 3.109 100</span> <span class="co"># es 2.1870 2.546 2.763 2.659 2.872 5.676 100</span>
<span class="co"># fr 1.8280 1.8960 3.214 1.9420 2.237 71.550 100</span> <span class="co"># fr 1.9880 2.339 2.609 2.456 2.636 5.197 100</span>
<span class="co"># it 1.9370 1.9970 2.163 2.0610 2.339 3.210 100</span> <span class="co"># it 2.2580 2.475 4.081 2.619 2.867 47.080 100</span>
<span class="co"># nl 1.9710 2.0280 2.698 2.1110 2.421 49.340 100</span> <span class="co"># nl 2.3120 2.535 2.792 2.664 2.822 8.113 100</span>
<span class="co"># pt 1.8920 1.9600 2.119 2.0200 2.261 3.265 100</span> <span class="co"># pt 2.1930 2.417 3.329 2.528 2.783 48.600 100</span>
<span class="co"># ru 1.8630 1.9420 2.779 2.0270 2.335 66.660 100</span> <span class="co"># ru 2.0470 2.360 2.596 2.481 2.683 6.030 100</span>
<span class="co"># sv 1.8680 1.9190 4.062 1.9890 2.263 78.870 100</span></code></pre></div> <span class="co"># sv 2.2030 2.443 3.077 2.545 2.703 43.350 100</span></code></pre></div>
<p>Currently supported languages are Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish.</p> <p>Currently supported languages are Danish, Dutch, English, French,
German, Italian, Portuguese, Russian, Spanish and Swedish.</p>
</div> </div>
</div> </div>
@ -374,12 +422,14 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
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</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -190,7 +190,7 @@
<div class="page-header toc-ignore"> <div class="page-header toc-ignore">
<h1 data-toc-skip>Data sets for download / own use</h1> <h1 data-toc-skip>Data sets for download / own use</h1>
<h4 data-toc-skip class="date">10 March 2022</h4> <h4 data-toc-skip class="date">14 March 2022</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small> <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<div class="hidden name"><code>datasets.Rmd</code></div> <div class="hidden name"><code>datasets.Rmd</code></div>

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</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

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</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -201,12 +201,17 @@
<div class="section level2"> <div class="section level2">
<h2 id="needed-r-packages">Needed R packages<a class="anchor" aria-label="anchor" href="#needed-r-packages"></a> <h2 id="needed-r-packages">Needed R packages<a class="anchor" aria-label="anchor" href="#needed-r-packages"></a>
</h2> </h2>
<p>As with many uses in R, we need some additional packages for AMR data analysis. Our package works closely together with the <a href="https://www.tidyverse.org" class="external-link">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/" class="external-link"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org" class="external-link"><code>ggplot2</code></a> by Dr Hadley Wickham. The tidyverse tremendously improves the way we conduct data science - it allows for a very natural way of writing syntaxes and creating beautiful plots in R.</p> <p>As with many uses in R, we need some additional packages for AMR data
<p>Our <code>AMR</code> package depends on these packages and even extends their use and functions.</p> analysis. Our package works closely together with the <a href="https://www.tidyverse.org" class="external-link">tidyverse packages</a> <a href="https://dplyr.tidyverse.org/" class="external-link"><code>dplyr</code></a> and <a href="https://ggplot2.tidyverse.org" class="external-link"><code>ggplot2</code></a> by Dr
Hadley Wickham. The tidyverse tremendously improves the way we conduct
data science - it allows for a very natural way of writing syntaxes and
creating beautiful plots in R.</p>
<p>Our <code>AMR</code> package depends on these packages and even
extends their use and functions.</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span> <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR">AMR</a></span><span class="op">)</span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="co"># (if not yet installed, install with:)</span> <span class="co"># (if not yet installed, install with:)</span>
<span class="co"># install.packages(c("tidyverse", "AMR"))</span></code></pre></div> <span class="co"># install.packages(c("tidyverse", "AMR"))</span></code></pre></div>
@ -214,7 +219,11 @@
<div class="section level2"> <div class="section level2">
<h2 id="prediction-analysis">Prediction analysis<a class="anchor" aria-label="anchor" href="#prediction-analysis"></a> <h2 id="prediction-analysis">Prediction analysis<a class="anchor" aria-label="anchor" href="#prediction-analysis"></a>
</h2> </h2>
<p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>, which takes the same input as functions for <a href="./AMR.html">other AMR data analysis</a>. Based on a date column, it calculates cases per year and uses a regression model to predict antimicrobial resistance.</p> <p>Our package contains a function <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>,
which takes the same input as functions for <a href="./AMR.html">other
AMR data analysis</a>. Based on a date column, it calculates cases per
year and uses a regression model to predict antimicrobial
resistance.</p>
<p>It is basically as easy as:</p> <p>It is basically as easy as:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></span> <div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># resistance prediction of piperacillin/tazobactam (TZP):</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">resistance_predict</span>(<span class="at">tbl =</span> example_isolates, <span class="at">col_date =</span> <span class="st">"date"</span>, <span class="at">col_ab =</span> <span class="st">"TZP"</span>, <span class="at">model =</span> <span class="st">"binomial"</span>)</span> <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="fu">resistance_predict</span>(<span class="at">tbl =</span> example_isolates, <span class="at">col_date =</span> <span class="st">"date"</span>, <span class="at">col_ab =</span> <span class="st">"TZP"</span>, <span class="at">model =</span> <span class="st">"binomial"</span>)</span>
@ -228,10 +237,16 @@
<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a>predict_TZP <span class="ot">&lt;-</span> example_isolates <span class="sc">%&gt;%</span> </span> <span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a>predict_TZP <span class="ot">&lt;-</span> example_isolates <span class="sc">%&gt;%</span> </span>
<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">resistance_predict</span>(<span class="at">col_ab =</span> <span class="st">"TZP"</span>,</span> <span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">resistance_predict</span>(<span class="at">col_ab =</span> <span class="st">"TZP"</span>,</span>
<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a> <span class="at">model =</span> <span class="st">"binomial"</span>)</span></code></pre></div> <span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a> <span class="at">model =</span> <span class="st">"binomial"</span>)</span></code></pre></div>
<p>The function will look for a date column itself if <code>col_date</code> is not set.</p> <p>The function will look for a date column itself if
<p>When running any of these commands, a summary of the regression model will be printed unless using <code>resistance_predict(..., info = FALSE)</code>.</p> <code>col_date</code> is not set.</p>
<p>When running any of these commands, a summary of the regression model
will be printed unless using
<code>resistance_predict(..., info = FALSE)</code>.</p>
<pre><code><span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre> <pre><code><span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre>
<p>This text is only a printed summary - the actual result (output) of the function is a <code>data.frame</code> containing for each year: the number of observations, the actual observed resistance, the estimated resistance and the standard error below and above the estimation:</p> <p>This text is only a printed summary - the actual result (output) of
the function is a <code>data.frame</code> containing for each year: the
number of observations, the actual observed resistance, the estimated
resistance and the standard error below and above the estimation:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">predict_TZP</span> <code class="sourceCode R"><span class="va">predict_TZP</span>
<span class="co"># year value se_min se_max observations observed estimated</span> <span class="co"># year value se_min se_max observations observed estimated</span>
@ -264,13 +279,20 @@
<span class="co"># 27 2028 0.43730688 0.3418075 0.5328063 NA NA 0.43730688</span> <span class="co"># 27 2028 0.43730688 0.3418075 0.5328063 NA NA 0.43730688</span>
<span class="co"># 28 2029 0.46175755 0.3597639 0.5637512 NA NA 0.46175755</span> <span class="co"># 28 2029 0.46175755 0.3597639 0.5637512 NA NA 0.46175755</span>
<span class="co"># 29 2030 0.48639359 0.3782932 0.5944939 NA NA 0.48639359</span> <span class="co"># 29 2030 0.48639359 0.3782932 0.5944939 NA NA 0.48639359</span>
<span class="co"># 30 2031 0.51109592 0.3973697 0.6248221 NA NA 0.51109592</span></code></pre></div> <span class="co"># 30 2031 0.51109592 0.3973697 0.6248221 NA NA 0.51109592</span>
<p>The function <code>plot</code> is available in base R, and can be extended by other packages to depend the output based on the type of input. We extended its function to cope with resistance predictions:</p> <span class="co"># 31 2032 0.53574417 0.4169574 0.6545309 NA NA 0.53574417</span></code></pre></div>
<p>The function <code>plot</code> is available in base R, and can be
extended by other packages to depend the output based on the type of
input. We extended its function to cope with resistance predictions:</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="fu"><a href="../reference/plot.html">plot</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p> <p><img src="resistance_predict_files/figure-html/unnamed-chunk-4-1.png" width="720"></p>
<p>This is the fastest way to plot the result. It automatically adds the right axes, error bars, titles, number of available observations and type of model.</p> <p>This is the fastest way to plot the result. It automatically adds the
<p>We also support the <code>ggplot2</code> package with our custom function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> to create more appealing plots:</p> right axes, error bars, titles, number of available observations and
type of model.</p>
<p>We also support the <code>ggplot2</code> package with our custom
function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> to create more appealing
plots:</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div> <code class="sourceCode R"><span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span></code></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p> <p><img src="resistance_predict_files/figure-html/unnamed-chunk-5-1.png" width="720"></p>
@ -282,7 +304,9 @@
<div class="section level3"> <div class="section level3">
<h3 id="choosing-the-right-model">Choosing the right model<a class="anchor" aria-label="anchor" href="#choosing-the-right-model"></a> <h3 id="choosing-the-right-model">Choosing the right model<a class="anchor" aria-label="anchor" href="#choosing-the-right-model"></a>
</h3> </h3>
<p>Resistance is not easily predicted; if we look at vancomycin resistance in Gram-positive bacteria, the spread (i.e. standard error) is enormous:</p> <p>Resistance is not easily predicted; if we look at vancomycin
resistance in Gram-positive bacteria, the spread (i.e. standard error)
is enormous:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
@ -290,8 +314,13 @@
<span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span> <span class="fu"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span><span class="op">(</span><span class="op">)</span>
<span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div> <span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p> <p><img src="resistance_predict_files/figure-html/unnamed-chunk-6-1.png" width="720"></p>
<p>Vancomycin resistance could be 100% in ten years, but might also stay around 0%.</p> <p>Vancomycin resistance could be 100% in ten years, but might also stay
<p>You can define the model with the <code>model</code> parameter. The model chosen above is a generalised linear regression model using a binomial distribution, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance.</p> around 0%.</p>
<p>You can define the model with the <code>model</code> parameter. The
model chosen above is a generalised linear regression model using a
binomial distribution, assuming that a period of zero resistance was
followed by a period of increasing resistance leading slowly to more and
more resistance.</p>
<p>Valid values are:</p> <p>Valid values are:</p>
<table class="table"> <table class="table">
<colgroup> <colgroup>
@ -307,7 +336,8 @@
<tbody> <tbody>
<tr class="odd"> <tr class="odd">
<td> <td>
<code>"binomial"</code> or <code>"binom"</code> or <code>"logit"</code> <code>"binomial"</code> or <code>"binom"</code> or
<code>"logit"</code>
</td> </td>
<td><code>glm(..., family = binomial)</code></td> <td><code>glm(..., family = binomial)</code></td>
<td>Generalised linear model with binomial distribution</td> <td>Generalised linear model with binomial distribution</td>
@ -328,7 +358,9 @@
</tr> </tr>
</tbody> </tbody>
</table> </table>
<p>For the vancomycin resistance in Gram-positive bacteria, a linear model might be more appropriate since no binomial distribution is to be expected based on the observed years:</p> <p>For the vancomycin resistance in Gram-positive bacteria, a linear
model might be more appropriate since no binomial distribution is to be
expected based on the observed years:</p>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <code class="sourceCode R"><span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="va">mo</span>, language <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Gram-positive"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span>
@ -337,7 +369,8 @@
<span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div> <span class="co"># ℹ Using column 'date' as input for `col_date`.</span></code></pre></div>
<p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p> <p><img src="resistance_predict_files/figure-html/unnamed-chunk-7-1.png" width="720"></p>
<p>This seems more likely, doesn’t it?</p> <p>This seems more likely, doesn’t it?</p>
<p>The model itself is also available from the object, as an <code>attribute</code>:</p> <p>The model itself is also available from the object, as an
<code>attribute</code>:</p>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> <div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span> <code class="sourceCode R"><span class="va">model</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/attributes.html" class="external-link">attributes</a></span><span class="op">(</span><span class="va">predict_TZP</span><span class="op">)</span><span class="op">$</span><span class="va">model</span>
@ -366,12 +399,14 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
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@ -44,7 +44,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -198,33 +198,83 @@
<p>Note: to keep the package size as small as possible, we only included this vignette on CRAN. You can read more vignettes on our website about how to conduct AMR data analysis, determine MDRO’s, find explanation of EUCAST rules, and much more: <a href="https://msberends.github.io/AMR/articles/" class="uri">https://msberends.github.io/AMR/articles/</a>.</p> <p>Note: to keep the package size as small as possible, we only included
this vignette on CRAN. You can read more vignettes on our website about
how to conduct AMR data analysis, determine MDRO’s, find explanation of
EUCAST rules, and much more: <a href="https://msberends.github.io/AMR/articles/" class="uri">https://msberends.github.io/AMR/articles/</a>.</p>
<hr> <hr>
<p><code>AMR</code> is a free, open-source and independent R package (see <a href="https://msberends.github.io/AMR/#copyright">Copyright</a>) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p> <p><code>AMR</code> is a free, open-source and independent R package
<p>After installing this package, R knows ~71,000 distinct microbial species and all ~570 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p> (see <a href="https://msberends.github.io/AMR/#copyright">Copyright</a>)
<p>The <code>AMR</code> package is available in Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.</p> to simplify the analysis and prediction of Antimicrobial Resistance
<p>This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. Since its first public release in early 2018, this package has been downloaded from more than 175 countries.</p> (AMR) and to work with microbial and antimicrobial data and properties,
by using evidence-based methods. <strong>Our aim is to provide a
standard</strong> for clean and reproducible antimicrobial resistance
data analysis, that can therefore empower epidemiological analyses to
continuously enable surveillance and treatment evaluation in any
setting.</p>
<p>After installing this package, R knows ~71,000 distinct microbial
species and all ~570 antibiotic, antimycotic and antiviral drugs by name
and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and
knows all about valid R/SI and MIC values. It supports any data format,
including WHONET/EARS-Net data.</p>
<p>The <code>AMR</code> package is available in Danish, Dutch, English,
French, German, Italian, Portuguese, Russian, Spanish and Swedish.
Antimicrobial drug (group) names and colloquial microorganism names are
provided in these languages.</p>
<p>This package is fully independent of any other R package and works on
Windows, macOS and Linux with all versions of R since R-3.0 (April
2013). <strong>It was designed to work in any setting, including those
with very limited resources</strong>. Since its first public release in
early 2018, this package has been downloaded from more than 175
countries.</p>
<p>This package can be used for:</p> <p>This package can be used for:</p>
<ul> <ul>
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life and List of Prokaryotic names with Standing in Nomenclature</li> <li>Reference for the taxonomy of microorganisms, since the package
<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines</li> contains all microbial (sub)species from the Catalogue of Life and List
<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records</li> of Prokaryotic names with Standing in Nomenclature</li>
<li>Interpreting raw MIC and disk diffusion values, based on the latest
CLSI or EUCAST guidelines</li>
<li>Retrieving antimicrobial drug names, doses and forms of
administration from clinical health care records</li>
<li>Determining first isolates to be used for AMR data analysis</li> <li>Determining first isolates to be used for AMR data analysis</li>
<li>Calculating antimicrobial resistance</li> <li>Calculating antimicrobial resistance</li>
<li>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)</li> <li>Determining multi-drug resistance (MDR) / multi-drug resistant
<li>Calculating (empirical) susceptibility of both mono therapy and combination therapies</li> organisms (MDRO)</li>
<li>Predicting future antimicrobial resistance using regression models</li> <li>Calculating (empirical) susceptibility of both mono therapy and
<li>Getting properties for any microorganism (like Gram stain, species, genus or family)</li> combination therapies</li>
<li>Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li> <li>Predicting future antimicrobial resistance using regression
models</li>
<li>Getting properties for any microorganism (like Gram stain, species,
genus or family)</li>
<li>Getting properties for any antibiotic (like name, code of
EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
<li>Plotting antimicrobial resistance</li> <li>Plotting antimicrobial resistance</li>
<li>Applying EUCAST expert rules</li> <li>Applying EUCAST expert rules</li>
<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code</li> <li>Getting SNOMED codes of a microorganism, or getting properties of a
<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code</li> microorganism based on a SNOMED code</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI</li> <li>Getting LOINC codes of an antibiotic, or getting properties of an
antibiotic based on a LOINC code</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2020 to
translate MIC values and disk diffusion diameters to R/SI</li>
<li>Principal component analysis for AMR</li> <li>Principal component analysis for AMR</li>
</ul> </ul>
<p>All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all download links on our website</a>, which is automatically updated with every code change.</p> <p>All reference data sets (about microorganisms, antibiotics, R/SI
<p>This R package was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>. This R package formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI 10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI 10.33612/diss.192486375</a>) but is actively and durably maintained (see <a href="https://msberends.github.io/AMR/news/index.html">changelog)</a>) by two public healthcare organisations in the Netherlands.</p> interpretation, EUCAST rules, etc.) in this <code>AMR</code> package are
publicly and freely available. We continually export our data sets to
formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat
files that are machine-readable and suitable for input in any software
program, such as laboratory information systems. Please find <a href="https://msberends.github.io/AMR/articles/datasets.html">all
download links on our website</a>, which is automatically updated with
every code change.</p>
<p>This R package was created for both routine data analysis and
academic research at the Faculty of Medical Sciences of the <a href="https://www.rug.nl" class="external-link">University of Groningen</a>, in collaboration
with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe
Medical Diagnostics and Advice Foundation</a> and <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>. This
R package formed the basis of two PhD theses (<a href="https://doi.org/10.33612/diss.177417131" class="external-link">DOI
10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI
10.33612/diss.192486375</a>) but is actively and durably maintained (see
<a href="https://msberends.github.io/AMR/news/index.html">changelog)</a>)
by two public healthcare organisations in the Netherlands.</p>
</div> </div>
<div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
@ -237,12 +287,14 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p> <p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p> <p></p>
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer> </footer>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/index.html
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@ -47,7 +47,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

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6
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@ -1,5 +1,5 @@
pandoc: 2.14.0.3 pandoc: 2.17.1.1
pkgdown: 2.0.0 pkgdown: 2.0.2
pkgdown_sha: ~ pkgdown_sha: ~
articles: articles:
AMR: AMR.html AMR: AMR.html
@ -12,7 +12,7 @@ articles:
datasets: datasets.html datasets: datasets.html
resistance_predict: resistance_predict.html resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html welcome_to_AMR: welcome_to_AMR.html
last_built: 2021-12-23T17:53Z last_built: 2022-03-14T15:33Z
urls: urls:
reference: https://msberends.github.io/AMR/reference reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles article: https://msberends.github.io/AMR/articles

8
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -184,11 +184,13 @@ The <a href="lifecycle.html">lifecycle</a> of this function is <strong>retired</
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

9
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,6 @@
<p>Welcome to the <code>AMR</code> package.</p> <p>Welcome to the <code>AMR</code> package.</p>
</div> </div>
<div id="ref-usage">Usage,NULL</div>
<div id="details"> <div id="details">
<h2>Details</h2> <h2>Details</h2>
@ -222,11 +221,13 @@ The Netherlands
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

8
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -195,11 +195,13 @@ This package contains <strong>all ~550 antibiotic, antimycotic and antiviral dru
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

12
docs/reference/WHONET.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,9 @@
<p>This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our <a href="example_isolates.html">example_isolates</a> data set. All patient names are created using online surname generators and are only in place for practice purposes.</p> <p>This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our <a href="example_isolates.html">example_isolates</a> data set. All patient names are created using online surname generators and are only in place for practice purposes.</p>
</div> </div>
<div id="ref-usage">Usage,<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">WHONET</span></code></pre></div></div> <div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">WHONET</span></code></pre></div>
</div>
<div id="format"> <div id="format">
<h2>Format</h2> <h2>Format</h2>
@ -213,11 +215,13 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/ab_property.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/age.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

8
docs/reference/antibiotics.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -259,11 +259,13 @@ This package contains <strong>all ~550 antibiotic, antimycotic and antiviral dru
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/as.disk.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -235,11 +235,13 @@ Function <code><a href="as.mo.html">as.mo()</a></code> to use the data for intel
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

8
docs/reference/catalogue_of_life_version.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -200,11 +200,13 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
docs/reference/count.html
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@ -18,7 +18,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/custom_eucast_rules.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

12
docs/reference/dosage.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,9 @@
<p>EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with <code><a href="eucast_rules.html">eucast_dosage()</a></code>.</p> <p>EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with <code><a href="eucast_rules.html">eucast_dosage()</a></code>.</p>
</div> </div>
<div id="ref-usage">Usage,<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">dosage</span></code></pre></div></div> <div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">dosage</span></code></pre></div>
</div>
<div id="format"> <div id="format">
<h2>Format</h2> <h2>Format</h2>
@ -200,11 +202,13 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
docs/reference/eucast_rules.html
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@ -18,7 +18,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

12
docs/reference/example_isolates.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,9 @@
<p>A data set containing 2,000 microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read <a href="https://msberends.github.io/AMR/articles/AMR.html">the tutorial on our website</a>.</p> <p>A data set containing 2,000 microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR data analysis. For examples, please read <a href="https://msberends.github.io/AMR/articles/AMR.html">the tutorial on our website</a>.</p>
</div> </div>
<div id="ref-usage">Usage,<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">example_isolates</span></code></pre></div></div> <div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">example_isolates</span></code></pre></div>
</div>
<div id="format"> <div id="format">
<h2>Format</h2> <h2>Format</h2>
@ -197,11 +199,13 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

12
docs/reference/example_isolates_unclean.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,9 @@
<p>A data set containing 3,000 microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.</p> <p>A data set containing 3,000 microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.</p>
</div> </div>
<div id="ref-usage">Usage,<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">example_isolates_unclean</span></code></pre></div></div> <div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">example_isolates_unclean</span></code></pre></div>
</div>
<div id="format"> <div id="format">
<h2>Format</h2> <h2>Format</h2>
@ -192,11 +194,13 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
docs/reference/first_isolate.html
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@ -18,7 +18,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

8
docs/reference/g.test.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -323,11 +323,13 @@ The <a href="lifecycle.html">lifecycle</a> of this function is <strong>questioni
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
docs/reference/get_episode.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/ggplot_pca.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/ggplot_rsi.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/guess_ab_col.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/index.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

12
docs/reference/intrinsic_resistant.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,9 @@
<p>Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.</p> <p>Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.</p>
</div> </div>
<div id="ref-usage">Usage,<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">intrinsic_resistant</span></code></pre></div></div> <div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">intrinsic_resistant</span></code></pre></div>
</div>
<div id="format"> <div id="format">
<h2>Format</h2> <h2>Format</h2>
@ -208,11 +210,13 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
docs/reference/italicise_taxonomy.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/join.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/key_antimicrobials.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/kurtosis.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/lifecycle.html
View File

@ -19,7 +19,7 @@ This page contains a section for every lifecycle (with text borrowed from the af
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/like.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/mdro.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

8
docs/reference/microorganisms.codes.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -203,11 +203,13 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

8
docs/reference/microorganisms.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -254,11 +254,13 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

8
docs/reference/microorganisms.old.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9004</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -210,11 +210,13 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
</div> </div>
</footer></div> </footer></div>

2
docs/reference/mo_matching_score.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/mo_property.html
View File

@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/mo_source.html
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@ -18,7 +18,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/pca.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/plot.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/proportion.html
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@ -18,7 +18,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/random.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/resistance_predict.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

12
docs/reference/rsi_translation.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>
@ -161,7 +161,9 @@
<p>Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2021) and CLSI (2010-2021). Use <code><a href="as.rsi.html">as.rsi()</a></code> to transform MICs or disks measurements to R/SI values.</p> <p>Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2021) and CLSI (2010-2021). Use <code><a href="as.rsi.html">as.rsi()</a></code> to transform MICs or disks measurements to R/SI values.</p>
</div> </div>
<div id="ref-usage">Usage,<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">rsi_translation</span></code></pre></div></div> <div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><span class="va">rsi_translation</span></code></pre></div>
</div>
<div id="format"> <div id="format">
<h2>Format</h2> <h2>Format</h2>
@ -206,11 +208,13 @@
<footer><div class="copyright"> <footer><div class="copyright">
<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p> <p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
</div> </div>
<div class="pkgdown"> <div class="pkgdown">
<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.0.</p> <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
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</footer></div> </footer></div>

2
docs/reference/skewness.html
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@ -18,7 +18,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/reference/translate.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a> <a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>

2
docs/survey.html
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@ -17,7 +17,7 @@
</button> </button>
<span class="navbar-brand"> <span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a> <a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span> <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
</span> </span>
</div> </div>