P281424
/
AMR
mirror of https://github.com/msberends/AMR.git
1
0
Fork 0
Code Releases Activity

(v0.8.0.9030) depend on tidyr >= 1.0.0

This commit is contained in:
dr. M.S. (Matthijs) Berends 2019-11-11 10:46:39 +01:00
parent d22834c5b8
commit 248b45da71
28 changed files with 580 additions and 515 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
DESCRIPTION
View File

@ -1,6 +1,6 @@
Package: AMR
Version: 0.8.0.9029
Date: 2019-11-10
Version: 0.8.0.9030
Date: 2019-11-11
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),
@ -47,7 +47,7 @@ Imports:
microbenchmark,
pillar,
rlang (>= 0.3.1),
tidyr (>= 0.7.0)
tidyr (>= 1.0.0)
Suggests:
covr (>= 3.0.1),
curl,

4
NAMESPACE
View File

@ -321,8 +321,8 @@ importFrom(stats,glm)
importFrom(stats,lm)
importFrom(stats,pchisq)
importFrom(stats,predict)
importFrom(tidyr,gather)
importFrom(tidyr,spread)
importFrom(tidyr,pivot_longer)
importFrom(tidyr,pivot_wider)
importFrom(utils,browseURL)
importFrom(utils,menu)
importFrom(utils,read.csv)

14
NEWS.md
View File

@ -1,8 +1,16 @@
# AMR 0.8.0.9029
<small>Last updated: 10-Nov-2019</small>
# AMR 0.8.0.9030
<small>Last updated: 11-Nov-2019</small>
### New
* Functions `susceptibility()` and `resistance()` as aliases of `proportion_SI()` and `proportion_R()`, respectively. These functions were added to make it more clear that I should be considered susceptible and not resistant.
* Functions `susceptibility()` and `resistance()` as aliases of `proportion_SI()` and `proportion_R()`, respectively. These functions were added to make it more clear that "I" should be considered susceptible and not resistant.
```r
library(dplyr)
example_isolates %>%
group_by(bug = mo_name(mo)) %>%
summarise(amoxicillin = resistance(AMX),
amox_clav = resistance(AMC)) %>%
filter(!is.na(amoxicillin) | !is.na(amox_clav))
```
* Support for a new MDRO guideline: Magiorakos AP, Srinivasan A *et al.* "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).
* This is now the new default guideline for the `mdro()` function
* The new Verbose mode (`mdro(...., verbose = TRUE)`) returns an informative data set where the reason for MDRO determination is given for every isolate, and an list of the resistant antimicrobial agents

13
R/bug_drug_combinations.R
View File

@ -32,7 +32,7 @@
#' @inheritParams rsi_df
#' @inheritParams base::formatC
#' @importFrom dplyr %>% rename group_by select mutate filter summarise ungroup
#' @importFrom tidyr spread
#' @importFrom tidyr pivot_longer
#' @details The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
#'
#' The language of the output can be overwritten with \code{options(AMR_locale)}, please see \link{translate}.
@ -80,7 +80,7 @@ bug_drug_combinations <- function(x,
FUN(...)) %>%
group_by(mo) %>%
select_if(is.rsi) %>%
gather("ab", "value", -mo) %>%
pivot_longer(-mo, names_to = "ab") %>%
group_by(mo, ab) %>%
summarise(S = sum(value == "S", na.rm = TRUE),
I = sum(value == "I", na.rm = TRUE),
@ -93,7 +93,7 @@ bug_drug_combinations <- function(x,
}
#' @importFrom dplyr everything rename %>% ungroup group_by summarise mutate_all arrange everything lag
#' @importFrom tidyr spread
#' @importFrom tidyr pivot_wider
#' @importFrom cleaner percentage
#' @exportMethod format.bug_drug_combinations
#' @export
@ -135,7 +135,7 @@ format.bug_drug_combinations <- function(x,
}
ab_txt
}
y <- x %>%
mutate(ab = as.ab(ab),
ab_txt = give_ab_name(ab = ab, format = translate_ab, language = language)) %>%
@ -146,8 +146,9 @@ format.bug_drug_combinations <- function(x,
mutate(txt = paste0(percentage(isolates / total, decimal.mark = decimal.mark, big.mark = big.mark),
" (", trimws(format(isolates, big.mark = big.mark)), "/",
trimws(format(total, big.mark = big.mark)), ")")) %>%
select(ab, ab_txt, mo, txt) %>%
spread(mo, txt) %>%
select(ab, ab_txt, mo, txt) %>%
arrange(mo) %>%
pivot_wider(names_from = mo, values_from = txt) %>%
mutate_all(~ifelse(is.na(.), "", .)) %>%
mutate(ab_group = ab_group(ab, language = language),
ab_txt) %>%

10
R/resistance_predict.R
View File

@ -29,12 +29,13 @@
#' @param year_every unit of sequence between lowest year found in the data and \code{year_max}
#' @param minimum minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.
#' @param model the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using \code{\link{glm}(..., family = \link{binomial})}), assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for all valid options.
#' @param I_as_S a logical to indicate whether values \code{I} should be treated as \code{S} (will otherwise be treated as \code{R})
#' @param I_as_S a logical to indicate whether values \code{I} should be treated as \code{S} (will otherwise be treated as \code{R}). The default, \code{TRUE}, follows the redefinition by EUCAST about the interpretion of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below.
#' @param preserve_measurements a logical to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.
#' @param info a logical to indicate whether textual analysis should be printed with the name and \code{\link{summary}} of the statistical model.
#' @param main title of the plot
#' @param ribbon a logical to indicate whether a ribbon should be shown (default) or error bars
#' @param ... parameters passed on to functions
#' @inheritSection as.rsi Interpretation of S, I and R
#' @inheritParams first_isolate
#' @inheritParams graphics::plot
#' @details Valid options for the statistical model are:
@ -59,6 +60,7 @@
#' @export
#' @importFrom stats predict glm lm
#' @importFrom dplyr %>% pull mutate mutate_at n group_by_at summarise filter filter_at all_vars n_distinct arrange case_when n_groups transmute ungroup
#' @importFrom tidyr pivot_wider
#' @inheritSection AMR Read more on our website!
#' @examples
#' x <- resistance_predict(example_isolates, col_ab = "AMX", year_min = 2010, model = "binomial")
@ -161,6 +163,7 @@ resistance_predict <- function(x,
}
year <- function(x) {
# don't depend on lubridate or so, would be overkill for only this function
if (all(grepl("^[0-9]{4}$", x))) {
x
} else {
@ -192,9 +195,12 @@ resistance_predict <- function(x,
}
colnames(df) <- c("year", "antibiotic", "observations")
df <- df %>%
filter(!is.na(antibiotic)) %>%
tidyr::spread(antibiotic, observations, fill = 0) %>%
pivot_wider(names_from = antibiotic,
values_from = observations,
values_fill = list(observations = 0)) %>%
filter((R + S) >= minimum)
df_matrix <- df %>%
ungroup() %>%

11
R/rsi_calc.R
View File

@ -167,8 +167,8 @@ rsi_calc <- function(...,
}
}
#' @importFrom dplyr %>% summarise_if mutate select everything bind_rows
#' @importFrom tidyr gather
#' @importFrom dplyr %>% summarise_if mutate select everything bind_rows arrange
#' @importFrom tidyr pivot_longer
rsi_calc_df <- function(type, # "proportion" or "count"
data,
translate_ab = "name",
@ -247,12 +247,13 @@ rsi_calc_df <- function(type, # "proportion" or "count"
}
res <- res %>%
gather(antibiotic, value, -interpretation, -data.groups) %>%
select(antibiotic, everything())
pivot_longer(-c(interpretation, data.groups), names_to = "antibiotic") %>%
select(antibiotic, everything()) %>%
arrange(antibiotic, interpretation)
if (!translate_ab == FALSE) {
res <- res %>% mutate(antibiotic = AMR::ab_property(antibiotic, property = translate_ab, language = language))
}
res
as.data.frame(res, stringsAsFactors = FALSE)
}

2
docs/404.html
View File

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/LICENSE-text.html
View File

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

556
docs/articles/AMR.html
View File

@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">10 November 2019</h4>
<h4 class="date">11 November 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -196,7 +196,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 10 November 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 11 November 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -212,21 +212,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-11-10</td>
<td align="center">2019-11-11</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2019-11-10</td>
<td align="center">2019-11-11</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2019-11-10</td>
<td align="center">2019-11-11</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -321,71 +321,71 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2015-05-08</td>
<td align="center">P3</td>
<td align="center">2011-09-25</td>
<td align="center">O7</td>
<td align="center">Hospital C</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">F</td>
</tr>
<tr class="even">
<td align="center">2012-04-04</td>
<td align="center">O9</td>
<td align="center">Hospital A</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">2015-03-11</td>
<td align="center">S3</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</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">2017-11-03</td>
<td align="center">Y8</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">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="odd">
<td align="center">2013-09-06</td>
<td align="center">U9</td>
<td align="center">Hospital B</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">F</td>
</tr>
<tr class="even">
<td align="center">2015-11-16</td>
<td align="center">E7</td>
<td align="center">2014-12-11</td>
<td align="center">G1</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">I</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>
</tr>
<tr class="odd">
<td align="center">2011-04-18</td>
<td align="center">F4</td>
<td align="center">Hospital B</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">S</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2010-04-22</td>
<td align="center">L4</td>
<td align="center">2013-01-02</td>
<td align="center">J8</td>
<td align="center">Hospital D</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">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="even">
<td align="center">2014-08-17</td>
<td align="center">S8</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>
</tbody>
</table>
<p>Now, let’s start the cleaning and the analysis!</p>
@ -406,8 +406,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,417 52.09% 10,417 52.09%
# 2 F 9,583 47.92% 20,000 100.00%</code></pre>
# 1 M 10,427 52.14% 10,427 52.14%
# 2 F 9,573 47.87% 20,000 100.00%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -437,14 +437,14 @@
<a class="sourceLine" id="cb14-18" data-line-number="18"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb14-19" data-line-number="19"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb14-20" data-line-number="20"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,545 values changed)</span></a>
<a class="sourceLine" id="cb14-21" data-line-number="21"><span class="co"># Streptococcus pneumoniae (1,552 values changed)</span></a>
<a class="sourceLine" id="cb14-22" data-line-number="22"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb14-23" data-line-number="23"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-24" data-line-number="24"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,309 values changed)</span></a>
<a class="sourceLine" id="cb14-25" data-line-number="25"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,279 values changed)</span></a>
<a class="sourceLine" id="cb14-26" data-line-number="26"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-27" data-line-number="27"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,733 values changed)</span></a>
<a class="sourceLine" id="cb14-28" data-line-number="28"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,800 values changed)</span></a>
<a class="sourceLine" id="cb14-29" data-line-number="29"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-30" data-line-number="30"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-31" data-line-number="31"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -452,23 +452,23 @@
<a class="sourceLine" id="cb14-33" data-line-number="33"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb14-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-35" data-line-number="35"><span class="co"># Other rules</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,194 values changed)</span></a>
<a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (121 values changed)</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S (2,257 values changed)</span></a>
<a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R (132 values changed)</span></a>
<a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S (no changes)</span></a>
<a class="sourceLine" id="cb14-42" data-line-number="42"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-43" data-line-number="43"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,489 out of 20,000 rows, making a total of 7,902 edits</span></a>
<a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># EUCAST rules affected 6,599 out of 20,000 rows, making a total of 8,020 edits</span></a>
<a class="sourceLine" id="cb14-45" data-line-number="45"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-46" data-line-number="46"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># =&gt; changed 7,902 test results</span></a>
<a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># - 118 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># - 4,776 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># - 1,063 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 318 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 1,603 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># =&gt; changed 8,020 test results</span></a>
<a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># - 119 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># - 4,832 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># - 1,096 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 342 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 1,607 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co"># - 24 test results changed from R to I</span></a>
<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co"># </span></a>
@ -497,8 +497,8 @@
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,696 first isolates (28.5% of total)</span></a></code></pre></div>
<p>So only 28.5% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,657 first isolates (28.3% of total)</span></a></code></pre></div>
<p>So only 28.3% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
<p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
@ -508,7 +508,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient P1, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient D2, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -524,19 +524,19 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-26</td>
<td align="center">P1</td>
<td align="center">2010-02-14</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</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">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-19</td>
<td align="center">P1</td>
<td align="center">2010-04-27</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -546,30 +546,30 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-04-24</td>
<td align="center">P1</td>
<td align="center">2010-05-31</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</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">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-06-11</td>
<td align="center">P1</td>
<td align="center">2010-08-21</td>
<td align="center">D2</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">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-11-24</td>
<td align="center">P1</td>
<td align="center">2010-09-21</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -579,8 +579,8 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-11</td>
<td align="center">P1</td>
<td align="center">2010-10-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -590,8 +590,8 @@
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-12-23</td>
<td align="center">P1</td>
<td align="center">2010-10-11</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -601,10 +601,10 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-01-14</td>
<td align="center">P1</td>
<td align="center">2010-11-16</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_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>
@ -612,26 +612,26 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-01-19</td>
<td align="center">P1</td>
<td align="center">2011-03-05</td>
<td align="center">D2</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">FALSE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-01-26</td>
<td align="center">P1</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-04-18</td>
<td align="center">D2</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">FALSE</td>
</tr>
</tbody>
</table>
<p>Only 2 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.</p>
@ -645,7 +645,7 @@
<a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,241 first weighted isolates (76.2% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,009 first weighted isolates (75.0% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -662,20 +662,20 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-01-26</td>
<td align="center">P1</td>
<td align="center">2010-02-14</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">I</td>
<td align="center">S</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">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-04-19</td>
<td align="center">P1</td>
<td align="center">2010-04-27</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -686,44 +686,44 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-04-24</td>
<td align="center">P1</td>
<td align="center">2010-05-31</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</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">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-06-11</td>
<td align="center">P1</td>
<td align="center">2010-08-21</td>
<td align="center">D2</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">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-11-24</td>
<td align="center">P1</td>
<td align="center">2010-09-21</td>
<td align="center">D2</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">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2010-12-11</td>
<td align="center">P1</td>
<td align="center">2010-10-04</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -734,8 +734,8 @@
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-12-23</td>
<td align="center">P1</td>
<td align="center">2010-10-11</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -746,10 +746,10 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-01-14</td>
<td align="center">P1</td>
<td align="center">2010-11-16</td>
<td align="center">D2</td>
<td align="center">B_ESCHR_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>
@ -758,35 +758,35 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-01-19</td>
<td align="center">P1</td>
<td align="center">2011-03-05</td>
<td align="center">D2</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">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-04-18</td>
<td align="center">D2</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">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-01-26</td>
<td align="center">P1</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 10 isolates are flagged. In total, 76.2% of all isolates are marked ‘first weighted’ - 47.7% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 2, now 8 isolates are flagged. In total, 75.0% of all isolates are marked ‘first weighted’ - 46.8% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,241 isolates for analysis.</p>
<p>So we end up with 15,009 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@ -812,57 +812,9 @@
<tbody>
<tr class="odd">
<td>1</td>
<td align="center">2015-05-08</td>
<td align="center">P3</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</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>
<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>3</td>
<td align="center">2013-09-06</td>
<td align="center">U9</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_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">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>5</td>
<td align="center">2011-04-18</td>
<td align="center">F4</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>7</td>
<td align="center">2016-10-10</td>
<td align="center">S10</td>
<td align="center">Hospital D</td>
<td align="center">2011-09-25</td>
<td align="center">O7</td>
<td align="center">Hospital C</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">S</td>
<td align="center">S</td>
@ -874,36 +826,84 @@
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>8</td>
<td align="center">2010-01-21</td>
<td align="center">R3</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<tr class="even">
<td>3</td>
<td align="center">2015-03-11</td>
<td align="center">S3</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_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">R</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">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>4</td>
<td align="center">2014-12-11</td>
<td align="center">G1</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">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>5</td>
<td align="center">2013-01-02</td>
<td align="center">J8</td>
<td align="center">Hospital D</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>7</td>
<td align="center">2013-08-06</td>
<td align="center">H4</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">I</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="even">
<td>9</td>
<td align="center">2011-11-23</td>
<td align="center">B7</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">2016-10-03</td>
<td align="center">F3</td>
<td align="center">Hospital D</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-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
</tbody>
@ -925,7 +925,7 @@
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,241 (of which NA: 0 = 0%)<br>
Length: 15,009 (of which NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -942,33 +942,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,593</td>
<td align="right">49.82%</td>
<td align="right">7,593</td>
<td align="right">49.82%</td>
<td align="right">7,411</td>
<td align="right">49.38%</td>
<td align="right">7,411</td>
<td align="right">49.38%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,734</td>
<td align="right">24.50%</td>
<td align="right">11,327</td>
<td align="right">74.32%</td>
<td align="right">3,707</td>
<td align="right">24.70%</td>
<td align="right">11,118</td>
<td align="right">74.08%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,327</td>
<td align="right">15.27%</td>
<td align="right">13,654</td>
<td align="right">89.59%</td>
<td align="right">2,318</td>
<td align="right">15.44%</td>
<td align="right">13,436</td>
<td align="right">89.52%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,587</td>
<td align="right">10.41%</td>
<td align="right">15,241</td>
<td align="right">1,573</td>
<td align="right">10.48%</td>
<td align="right">15,009</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -980,7 +980,7 @@ Longest: 24</p>
<p>The functions <code><a href="../reference/proportion.html">resistance()</a></code> and <code><a href="../reference/proportion.html">susceptibility()</a></code> can be used to calculate antimicrobial resistance or susceptibility. For more specific analyses, the functions <code><a href="../reference/proportion.html">proportion_S()</a></code>, <code><a href="../reference/proportion.html">proportion_SI()</a></code>, <code><a href="../reference/proportion.html">proportion_I()</a></code>, <code><a href="../reference/proportion.html">proportion_IR()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code> can be used to determine the proportion of a specific antimicrobial outcome.</p>
<p>As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a></code>, equal to <code><a href="../reference/proportion.html">resistance()</a></code>) and susceptibility as the proportion of S and I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to <code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their own:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/proportion.html">resistance</a></span>(AMX)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4724099</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4684523</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -993,19 +993,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4637681</td>
<td align="center">0.4640823</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4776811</td>
<td align="center">0.4663609</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4811697</td>
<td align="center">0.4736130</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4694820</td>
<td align="center">0.4749499</td>
</tr>
</tbody>
</table>
@ -1023,23 +1023,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4637681</td>
<td align="center">4554</td>
<td align="center">0.4640823</td>
<td align="center">4566</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4776811</td>
<td align="center">5399</td>
<td align="center">0.4663609</td>
<td align="center">5232</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4811697</td>
<td align="center">2257</td>
<td align="center">0.4736130</td>
<td align="center">2217</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4694820</td>
<td align="center">3031</td>
<td align="center">0.4749499</td>
<td align="center">2994</td>
</tr>
</tbody>
</table>
@ -1059,27 +1059,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9212433</td>
<td align="center">0.8984591</td>
<td align="center">0.9927565</td>
<td align="center">0.9211982</td>
<td align="center">0.8896235</td>
<td align="center">0.9929834</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.8298677</td>
<td align="center">0.8897290</td>
<td align="center">0.9836169</td>
<td align="center">0.8239034</td>
<td align="center">0.8804832</td>
<td align="center">0.9809282</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9290305</td>
<td align="center">0.9258168</td>
<td align="center">0.9946438</td>
<td align="center">0.9188023</td>
<td align="center">0.9209603</td>
<td align="center">0.9932560</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6067899</td>
<td align="center">0.5974978</td>
<td align="center">0.0000000</td>
<td align="center">0.6067899</td>
<td align="center">0.5974978</td>
</tr>
</tbody>
</table>
@ -1089,11 +1089,12 @@ Longest: 24</p>
<a class="sourceLine" id="cb29-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="st">"1. Amoxi/clav"</span> =<span class="st"> </span><span class="kw"><a href="../reference/proportion.html">susceptibility</a></span>(AMC),</a>
<a class="sourceLine" id="cb29-4" data-line-number="4"> <span class="st">"2. Gentamicin"</span> =<span class="st"> </span><span class="kw"><a href="../reference/proportion.html">susceptibility</a></span>(GEN),</a>
<a class="sourceLine" id="cb29-5" data-line-number="5"> <span class="st">"3. Amoxi/clav + genta"</span> =<span class="st"> </span><span class="kw"><a href="../reference/proportion.html">susceptibility</a></span>(AMC, GEN)) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb29-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/gather.html">gather</a></span>(<span class="st">"antibiotic"</span>, <span class="st">"S"</span>, <span class="op">-</span>genus) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb29-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(<span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> genus,</a>
<a class="sourceLine" id="cb29-8" data-line-number="8"> <span class="dt">y =</span> S,</a>
<a class="sourceLine" id="cb29-9" data-line-number="9"> <span class="dt">fill =</span> antibiotic)) <span class="op">+</span></a>
<a class="sourceLine" id="cb29-10" data-line-number="10"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html">geom_col</a></span>(<span class="dt">position =</span> <span class="st">"dodge2"</span>)</a></code></pre></div>
<a class="sourceLine" id="cb29-6" data-line-number="6"><span class="st"> </span><span class="co"># pivot_longer() from the tidyr package "lengthens" data:</span></a>
<a class="sourceLine" id="cb29-7" data-line-number="7"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html">pivot_longer</a></span>(<span class="op">-</span>genus, <span class="dt">names_to =</span> <span class="st">"antibiotic"</span>) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb29-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot</a></span>(<span class="kw"><a href="https://ggplot2.tidyverse.org/reference/aes.html">aes</a></span>(<span class="dt">x =</span> genus,</a>
<a class="sourceLine" id="cb29-9" data-line-number="9"> <span class="dt">y =</span> value,</a>
<a class="sourceLine" id="cb29-10" data-line-number="10"> <span class="dt">fill =</span> antibiotic)) <span class="op">+</span></a>
<a class="sourceLine" id="cb29-11" data-line-number="11"><span class="st"> </span><span class="kw"><a href="https://ggplot2.tidyverse.org/reference/geom_bar.html">geom_col</a></span>(<span class="dt">position =</span> <span class="st">"dodge2"</span>)</a></code></pre></div>
<p><img src="AMR_files/figure-html/plot%201-1.png" width="720"></p>
</div>
<div id="plots" class="section level2">
@ -1154,19 +1155,24 @@ Longest: 24</p>
<a href="#independence-test" class="anchor"></a>Independence test</h2>
<p>The next example uses the included <code>example_isolates</code>, which is an anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. This <code>data.frame</code> can be used to practice AMR analysis.</p>
<p>We will compare the resistance to fosfomycin (column <code>FOS</code>) in hospital A and D. The input for the <code><a href="https://rdrr.io/r/stats/fisher.test.html">fisher.test()</a></code> can be retrieved with a transformation like this:</p>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" data-line-number="1">check_FOS &lt;-<span class="st"> </span>example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(hospital_id <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"A"</span>, <span class="st">"D"</span>)) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># filter on only hospitals A and D</span></a>
<a class="sourceLine" id="cb34-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(hospital_id, FOS) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># select the hospitals and fosfomycin</span></a>
<a class="sourceLine" id="cb34-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># group on the hospitals</span></a>
<a class="sourceLine" id="cb34-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_df</a></span>(<span class="dt">combine_SI =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># count all isolates per group (hospital_id)</span></a>
<a class="sourceLine" id="cb34-6" data-line-number="6"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/spread.html">spread</a></span>(hospital_id, value) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># transform output so A and D are columns</span></a>
<a class="sourceLine" id="cb34-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(A, D) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># and select these only</span></a>
<a class="sourceLine" id="cb34-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span>() <span class="co"># transform to good old matrix for fisher.test()</span></a>
<a class="sourceLine" id="cb34-9" data-line-number="9"></a>
<a class="sourceLine" id="cb34-10" data-line-number="10">check_FOS</a>
<a class="sourceLine" id="cb34-11" data-line-number="11"><span class="co"># A D</span></a>
<a class="sourceLine" id="cb34-12" data-line-number="12"><span class="co"># [1,] 25 77</span></a>
<a class="sourceLine" id="cb34-13" data-line-number="13"><span class="co"># [2,] 24 33</span></a></code></pre></div>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" data-line-number="1"><span class="co"># use package 'tidyr' to pivot data; </span></a>
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="co"># it gets installed with this 'AMR' package</span></a>
<a class="sourceLine" id="cb34-3" data-line-number="3"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(tidyr)</a>
<a class="sourceLine" id="cb34-4" data-line-number="4"></a>
<a class="sourceLine" id="cb34-5" data-line-number="5">check_FOS &lt;-<span class="st"> </span>example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb34-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(hospital_id <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"A"</span>, <span class="st">"D"</span>)) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># filter on only hospitals A and D</span></a>
<a class="sourceLine" id="cb34-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(hospital_id, FOS) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># select the hospitals and fosfomycin</span></a>
<a class="sourceLine" id="cb34-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># group on the hospitals</span></a>
<a class="sourceLine" id="cb34-9" data-line-number="9"><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_df</a></span>(<span class="dt">combine_SI =</span> <span class="ot">TRUE</span>) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># count all isolates per group (hospital_id)</span></a>
<a class="sourceLine" id="cb34-10" data-line-number="10"><span class="st"> </span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/pivot_wider.html">pivot_wider</a></span>(<span class="dt">names_from =</span> hospital_id, <span class="co"># transform output so A and D are columns</span></a>
<a class="sourceLine" id="cb34-11" data-line-number="11"> <span class="dt">values_from =</span> value) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb34-12" data-line-number="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(A, D) <span class="op">%&gt;%</span><span class="st"> </span><span class="co"># and only select these columns</span></a>
<a class="sourceLine" id="cb34-13" data-line-number="13"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span>() <span class="co"># transform to a good old matrix for fisher.test()</span></a>
<a class="sourceLine" id="cb34-14" data-line-number="14"></a>
<a class="sourceLine" id="cb34-15" data-line-number="15">check_FOS</a>
<a class="sourceLine" id="cb34-16" data-line-number="16"><span class="co"># A D</span></a>
<a class="sourceLine" id="cb34-17" data-line-number="17"><span class="co"># [1,] 25 77</span></a>
<a class="sourceLine" id="cb34-18" data-line-number="18"><span class="co"># [2,] 24 33</span></a></code></pre></div>
<p>We can apply the test now with:</p>
<div class="sourceCode" id="cb35"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb35-1" data-line-number="1"><span class="co"># do Fisher's Exact Test</span></a>
<a class="sourceLine" id="cb35-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/stats/fisher.test.html">fisher.test</a></span>(check_FOS) </a>
@ -1181,7 +1187,7 @@ Longest: 24</p>
<a class="sourceLine" id="cb35-11" data-line-number="11"><span class="co"># sample estimates:</span></a>
<a class="sourceLine" id="cb35-12" data-line-number="12"><span class="co"># odds ratio </span></a>
<a class="sourceLine" id="cb35-13" data-line-number="13"><span class="co"># 0.4488318</span></a></code></pre></div>
<p>As can be seen, the p value is 0.031, which means that the fosfomycin resistances found in hospital A and D are really different.</p>
<p>As can be seen, the p value is 0.031, which means that the fosfomycin resistance found in hospital A and D are really different.</p>
</div>
</div>
</div>

BIN
docs/articles/AMR_files/figure-html/plot 1-1.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 64 KiB

After

Width:  |  Height:  |  Size: 64 KiB

BIN
docs/articles/AMR_files/figure-html/plot 3-1.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 51 KiB

After

Width:  |  Height:  |  Size: 51 KiB

BIN
docs/articles/AMR_files/figure-html/plot 4-1.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 102 KiB

After

Width:  |  Height:  |  Size: 102 KiB

BIN
docs/articles/AMR_files/figure-html/plot 5-1.png
View File

Binary file not shown.
Side by Side Swipe Overlay

Before

Width:  |  Height:  |  Size: 83 KiB

After

Width:  |  Height:  |  Size: 83 KiB

6
docs/articles/SPSS.html
View File

@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">16 October 2019</h4>
<h4 class="date">11 November 2019</h4>
<div class="hidden name"><code>SPSS.Rmd</code></div>
@ -213,7 +213,7 @@
</li>
<li>
<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, gathering, 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>
<p><strong>R can be easily automated.</strong></p>

2
docs/articles/index.html
View File

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/authors.html
View File

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/index.html
View File

@ -45,7 +45,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

398
docs/news/index.html
View File

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>
@ -231,16 +231,24 @@
</div>
<div id="amr-0-8-0-9029" class="section level1">
<div id="amr-0-8-0-9030" class="section level1">
<h1 class="page-header">
<a href="#amr-0-8-0-9029" class="anchor"></a>AMR 0.8.0.9029<small> Unreleased </small>
<a href="#amr-0-8-0-9030" class="anchor"></a>AMR 0.8.0.9030<small> Unreleased </small>
</h1>
<p><small>Last updated: 10-Nov-2019</small></p>
<p><small>Last updated: 11-Nov-2019</small></p>
<div id="new" class="section level3">
<h3 class="hasAnchor">
<a href="#new" class="anchor"></a>New</h3>
<ul>
<li>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that I should be considered susceptible and not resistant.</li>
<li>
<p>Functions <code><a href="../reference/proportion.html">susceptibility()</a></code> and <code><a href="../reference/proportion.html">resistance()</a></code> as aliases of <code><a href="../reference/proportion.html">proportion_SI()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2">example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb1-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(<span class="dt">bug =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(mo)) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb1-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise</a></span>(<span class="dt">amoxicillin =</span> <span class="kw"><a href="../reference/proportion.html">resistance</a></span>(AMX),</a>
<a class="sourceLine" id="cb1-5" data-line-number="5"> <span class="dt">amox_clav =</span> <span class="kw"><a href="../reference/proportion.html">resistance</a></span>(AMC)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="op">!</span><span class="kw"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span>(amoxicillin) <span class="op">|</span><span class="st"> </span><span class="op">!</span><span class="kw"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span>(amox_clav))</a></code></pre></div>
</li>
<li>Support for a new MDRO guideline: 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).
<ul>
<li>This is now the new default guideline for the <code><a href="../reference/mdro.html">mdro()</a></code> function</li>
@ -287,21 +295,21 @@
<ul>
<li>
<p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new parameter <code>include_unknown</code>:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(..., <span class="dt">include_unknown =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(..., <span class="dt">include_unknown =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</li>
<li>
<p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="co"># how it works in base R:</span></a>
<a class="sourceLine" id="cb2-2" data-line-number="2">x &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="st">"A"</span>)</a>
<a class="sourceLine" id="cb2-3" data-line-number="3">x[<span class="dv">1</span>] &lt;-<span class="st"> "B"</span></a>
<a class="sourceLine" id="cb2-4" data-line-number="4"><span class="co">#&gt; Warning message:</span></a>
<a class="sourceLine" id="cb2-5" data-line-number="5"><span class="co">#&gt; invalid factor level, NA generated</span></a>
<a class="sourceLine" id="cb2-6" data-line-number="6"></a>
<a class="sourceLine" id="cb2-7" data-line-number="7"><span class="co"># how it now works similarly for classes 'mo' and 'ab':</span></a>
<a class="sourceLine" id="cb2-8" data-line-number="8">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb2-9" data-line-number="9">x[<span class="dv">1</span>] &lt;-<span class="st"> "testvalue"</span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"><span class="co">#&gt; Warning message:</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co">#&gt; invalid microorganism code, NA generated</span></a></code></pre></div>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="co"># how it works in base R:</span></a>
<a class="sourceLine" id="cb3-2" data-line-number="2">x &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/factor.html">factor</a></span>(<span class="st">"A"</span>)</a>
<a class="sourceLine" id="cb3-3" data-line-number="3">x[<span class="dv">1</span>] &lt;-<span class="st"> "B"</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co">#&gt; Warning message:</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co">#&gt; invalid factor level, NA generated</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co"># how it now works similarly for classes 'mo' and 'ab':</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb3-9" data-line-number="9">x[<span class="dv">1</span>] &lt;-<span class="st"> "testvalue"</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co">#&gt; Warning message:</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co">#&gt; invalid microorganism code, NA generated</span></a></code></pre></div>
This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code><a href="../reference/mo_property.html">mo_name()</a></code>, although the class would suggest a valid microbial code.</li>
<li>Function <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq()</a></code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</li>
<li><p>Renamed data set <code>septic_patients</code> to <code>example_isolates</code></p></li>
@ -313,55 +321,55 @@ This is important, because a value like <code>"testvalue"</code> could never be
<ul>
<li>
<p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(example_isolates)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3">x[<span class="dv">1</span><span class="op">:</span><span class="dv">4</span>, ]</a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co">#&gt; mo ab S I R total</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co">#&gt; 1 A. baumannii AMC 0 0 3 3</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co">#&gt; 2 A. baumannii AMK 0 0 0 0</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co">#&gt; 3 A. baumannii AMP 0 0 3 3</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co">#&gt; 4 A. baumannii AMX 0 0 3 3</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Use 'format()' on this result to get a publicable/printable format.</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># change the transformation with the FUN argument to anything you like:</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(example_isolates, <span class="dt">FUN =</span> mo_gramstain)</a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14">x[<span class="dv">1</span><span class="op">:</span><span class="dv">4</span>, ]</a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co">#&gt; mo ab S I R total</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co">#&gt; 1 Gram-negative AMC 469 89 174 732</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co">#&gt; 2 Gram-negative AMK 251 0 2 253</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co">#&gt; 3 Gram-negative AMP 227 0 405 632</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co">#&gt; 4 Gram-negative AMX 227 0 405 632</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Use 'format()' on this result to get a publicable/printable format.</span></a></code></pre></div>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(example_isolates)</a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3">x[<span class="dv">1</span><span class="op">:</span><span class="dv">4</span>, ]</a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="co">#&gt; mo ab S I R total</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="co">#&gt; 1 A. baumannii AMC 0 0 3 3</span></a>
<a class="sourceLine" id="cb4-6" data-line-number="6"><span class="co">#&gt; 2 A. baumannii AMK 0 0 0 0</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="co">#&gt; 3 A. baumannii AMP 0 0 3 3</span></a>
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="co">#&gt; 4 A. baumannii AMX 0 0 3 3</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Use 'format()' on this result to get a publicable/printable format.</span></a>
<a class="sourceLine" id="cb4-10" data-line-number="10"></a>
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="co"># change the transformation with the FUN argument to anything you like:</span></a>
<a class="sourceLine" id="cb4-12" data-line-number="12">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(example_isolates, <span class="dt">FUN =</span> mo_gramstain)</a>
<a class="sourceLine" id="cb4-13" data-line-number="13"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb4-14" data-line-number="14">x[<span class="dv">1</span><span class="op">:</span><span class="dv">4</span>, ]</a>
<a class="sourceLine" id="cb4-15" data-line-number="15"><span class="co">#&gt; mo ab S I R total</span></a>
<a class="sourceLine" id="cb4-16" data-line-number="16"><span class="co">#&gt; 1 Gram-negative AMC 469 89 174 732</span></a>
<a class="sourceLine" id="cb4-17" data-line-number="17"><span class="co">#&gt; 2 Gram-negative AMK 251 0 2 253</span></a>
<a class="sourceLine" id="cb4-18" data-line-number="18"><span class="co">#&gt; 3 Gram-negative AMP 227 0 405 632</span></a>
<a class="sourceLine" id="cb4-19" data-line-number="19"><span class="co">#&gt; 4 Gram-negative AMX 227 0 405 632</span></a>
<a class="sourceLine" id="cb4-20" data-line-number="20"><span class="co">#&gt; </span><span class="al">NOTE</span><span class="co">: Use 'format()' on this result to get a publicable/printable format.</span></a></code></pre></div>
<p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://rdrr.io/r/base/format.html">format()</a></code> function:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/format.html">format</a></span>(x, <span class="dt">combine_IR =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/format.html">format</a></span>(x, <span class="dt">combine_IR =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
</li>
<li>
<p>Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="co"># --------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="co"># only_all_tested = FALSE only_all_tested = TRUE</span></a>
<a class="sourceLine" id="cb5-3" data-line-number="3"><span class="co"># ----------------------- -----------------------</span></a>
<a class="sourceLine" id="cb5-4" data-line-number="4"><span class="co"># Drug A Drug B include as include as include as include as</span></a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="co"># numerator denominator numerator denominator</span></a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># -------- -------- ---------- ----------- ---------- -----------</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># S or I S or I X X X X</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># R S or I X X X X</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># &lt;NA&gt; S or I X X - -</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># S or I R X X X X</span></a>
<a class="sourceLine" id="cb5-11" data-line-number="11"><span class="co"># R R - X - X</span></a>
<a class="sourceLine" id="cb5-12" data-line-number="12"><span class="co"># &lt;NA&gt; R - - - -</span></a>
<a class="sourceLine" id="cb5-13" data-line-number="13"><span class="co"># S or I &lt;NA&gt; X X - -</span></a>
<a class="sourceLine" id="cb5-14" data-line-number="14"><span class="co"># R &lt;NA&gt; - - - -</span></a>
<a class="sourceLine" id="cb5-15" data-line-number="15"><span class="co"># &lt;NA&gt; &lt;NA&gt; - - - -</span></a>
<a class="sourceLine" id="cb5-16" data-line-number="16"><span class="co"># --------------------------------------------------------------------</span></a></code></pre></div>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="co"># --------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb6-2" data-line-number="2"><span class="co"># only_all_tested = FALSE only_all_tested = TRUE</span></a>
<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="co"># ----------------------- -----------------------</span></a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="co"># Drug A Drug B include as include as include as include as</span></a>
<a class="sourceLine" id="cb6-5" data-line-number="5"><span class="co"># numerator denominator numerator denominator</span></a>
<a class="sourceLine" id="cb6-6" data-line-number="6"><span class="co"># -------- -------- ---------- ----------- ---------- -----------</span></a>
<a class="sourceLine" id="cb6-7" data-line-number="7"><span class="co"># S or I S or I X X X X</span></a>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="co"># R S or I X X X X</span></a>
<a class="sourceLine" id="cb6-9" data-line-number="9"><span class="co"># &lt;NA&gt; S or I X X - -</span></a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="co"># S or I R X X X X</span></a>
<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># R R - X - X</span></a>
<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># &lt;NA&gt; R - - - -</span></a>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># S or I &lt;NA&gt; X X - -</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># R &lt;NA&gt; - - - -</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># &lt;NA&gt; &lt;NA&gt; - - - -</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># --------------------------------------------------------------------</span></a></code></pre></div>
Since this is a major change, usage of the old <code>also_single_tested</code> will throw an informative error that it has been replaced by <code>only_all_tested</code>.</li>
<li>
<p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code> <code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="co"># (run this on your own console, as this page does not support colour printing)</span></a>
<a class="sourceLine" id="cb6-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb6-3" data-line-number="3">example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(mo<span class="op">:</span>AMC) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb6-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">as_tibble</a></span>()</a></code></pre></div>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1"><span class="co"># (run this on your own console, as this page does not support colour printing)</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr)</a>
<a class="sourceLine" id="cb7-3" data-line-number="3">example_isolates <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(mo<span class="op">:</span>AMC) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/reexports.html">as_tibble</a></span>()</a></code></pre></div>
</li>
</ul>
</div>
@ -438,14 +446,14 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<ul>
<li>
<p>Function <code><a href="../reference/proportion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(AMX, CIP) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/proportion.html">rsi_df</a></span>()</a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="co"># antibiotic interpretation value isolates</span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># 1 Amoxicillin SI 0.4442636 546</span></a>
<a class="sourceLine" id="cb7-6" data-line-number="6"><span class="co"># 2 Amoxicillin R 0.5557364 683</span></a>
<a class="sourceLine" id="cb7-7" data-line-number="7"><span class="co"># 3 Ciprofloxacin SI 0.8381831 1181</span></a>
<a class="sourceLine" id="cb7-8" data-line-number="8"><span class="co"># 4 Ciprofloxacin R 0.1618169 228</span></a></code></pre></div>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(AMX, CIP) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb8-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/proportion.html">rsi_df</a></span>()</a>
<a class="sourceLine" id="cb8-4" data-line-number="4"><span class="co"># antibiotic interpretation value isolates</span></a>
<a class="sourceLine" id="cb8-5" data-line-number="5"><span class="co"># 1 Amoxicillin SI 0.4442636 546</span></a>
<a class="sourceLine" id="cb8-6" data-line-number="6"><span class="co"># 2 Amoxicillin R 0.5557364 683</span></a>
<a class="sourceLine" id="cb8-7" data-line-number="7"><span class="co"># 3 Ciprofloxacin SI 0.8381831 1181</span></a>
<a class="sourceLine" id="cb8-8" data-line-number="8"><span class="co"># 4 Ciprofloxacin R 0.1618169 228</span></a></code></pre></div>
</li>
<li>
<p>Support for all scientifically published pathotypes of <em>E. coli</em> to date (that we could find). Supported are:</p>
@ -463,12 +471,12 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<li>UPEC (Uropathogenic <em>E. coli</em>)</li>
</ul>
<p>All these lead to the microbial ID of <em>E. coli</em>:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="co"># B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb8-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb8-4" data-line-number="4"><span class="co"># "Escherichia coli"</span></a>
<a class="sourceLine" id="cb8-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"EHEC"</span>)</a>
<a class="sourceLine" id="cb8-6" data-line-number="6"><span class="co"># "Gram-negative"</span></a></code></pre></div>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="co"># B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb9-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb9-4" data-line-number="4"><span class="co"># "Escherichia coli"</span></a>
<a class="sourceLine" id="cb9-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"EHEC"</span>)</a>
<a class="sourceLine" id="cb9-6" data-line-number="6"><span class="co"># "Gram-negative"</span></a></code></pre></div>
</li>
<li>Function <code><a href="../reference/mo_property.html">mo_info()</a></code> as an analogy to <code><a href="../reference/ab_property.html">ab_info()</a></code>. The <code><a href="../reference/mo_property.html">mo_info()</a></code> prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism</li>
<li><p>Function <code><a href="../reference/mo_property.html">mo_synonyms()</a></code> to get all previously accepted taxonomic names of a microorganism</p></li>
@ -567,14 +575,14 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=Tra
<li>when all values are unique it now shows a message instead of a warning</li>
<li>
<p>support for boxplots:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(age) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span>()</a>
<a class="sourceLine" id="cb9-4" data-line-number="4"><span class="co"># grouped boxplots:</span></a>
<a class="sourceLine" id="cb9-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(age) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb9-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span>()</a></code></pre></div>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(age) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span>()</a>
<a class="sourceLine" id="cb10-4" data-line-number="4"><span class="co"># grouped boxplots:</span></a>
<a class="sourceLine" id="cb10-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb10-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb10-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(age) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb10-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/graphics/boxplot.html">boxplot</a></span>()</a></code></pre></div>
</li>
</ul>
</li>
@ -659,32 +667,32 @@ This data is updated annually - check the included version with the new function
</li>
<li>
<p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1"><span class="kw"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span>()</a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="kw"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span>()</a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="kw"><a href="../reference/filter_ab_class.html">filter_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-4" data-line-number="4"><span class="kw"><a href="../reference/filter_ab_class.html">filter_1st_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-5" data-line-number="5"><span class="kw"><a href="../reference/filter_ab_class.html">filter_2nd_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-6" data-line-number="6"><span class="kw"><a href="../reference/filter_ab_class.html">filter_3rd_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-7" data-line-number="7"><span class="kw"><a href="../reference/filter_ab_class.html">filter_4th_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-8" data-line-number="8"><span class="kw"><a href="../reference/filter_ab_class.html">filter_fluoroquinolones</a></span>()</a>
<a class="sourceLine" id="cb10-9" data-line-number="9"><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>()</a>
<a class="sourceLine" id="cb10-10" data-line-number="10"><span class="kw"><a href="../reference/filter_ab_class.html">filter_macrolides</a></span>()</a>
<a class="sourceLine" id="cb10-11" data-line-number="11"><span class="kw"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span>()</a></code></pre></div>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1"><span class="kw"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span>()</a>
<a class="sourceLine" id="cb11-2" data-line-number="2"><span class="kw"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span>()</a>
<a class="sourceLine" id="cb11-3" data-line-number="3"><span class="kw"><a href="../reference/filter_ab_class.html">filter_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb11-4" data-line-number="4"><span class="kw"><a href="../reference/filter_ab_class.html">filter_1st_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb11-5" data-line-number="5"><span class="kw"><a href="../reference/filter_ab_class.html">filter_2nd_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb11-6" data-line-number="6"><span class="kw"><a href="../reference/filter_ab_class.html">filter_3rd_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb11-7" data-line-number="7"><span class="kw"><a href="../reference/filter_ab_class.html">filter_4th_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb11-8" data-line-number="8"><span class="kw"><a href="../reference/filter_ab_class.html">filter_fluoroquinolones</a></span>()</a>
<a class="sourceLine" id="cb11-9" data-line-number="9"><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>()</a>
<a class="sourceLine" id="cb11-10" data-line-number="10"><span class="kw"><a href="../reference/filter_ab_class.html">filter_macrolides</a></span>()</a>
<a class="sourceLine" id="cb11-11" data-line-number="11"><span class="kw"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span>()</a></code></pre></div>
<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(<span class="dt">result =</span> <span class="st">"R"</span>)</a>
<a class="sourceLine" id="cb11-2" data-line-number="2"><span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span></a>
<a class="sourceLine" id="cb11-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(<span class="dt">result =</span> <span class="st">"R"</span>, <span class="dt">scope =</span> <span class="st">"all"</span>)</a>
<a class="sourceLine" id="cb11-4" data-line-number="4"><span class="co"># Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</span></a></code></pre></div>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(<span class="dt">result =</span> <span class="st">"R"</span>)</a>
<a class="sourceLine" id="cb12-2" data-line-number="2"><span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span></a>
<a class="sourceLine" id="cb12-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(<span class="dt">result =</span> <span class="st">"R"</span>, <span class="dt">scope =</span> <span class="st">"all"</span>)</a>
<a class="sourceLine" id="cb12-4" data-line-number="4"><span class="co"># Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</span></a></code></pre></div>
</li>
<li>
<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">ab_property -&gt;<span class="st"> </span><span class="kw">atc_property</span>()</a>
<a class="sourceLine" id="cb12-2" data-line-number="2">ab_name -&gt;<span class="st"> </span><span class="kw">atc_name</span>()</a>
<a class="sourceLine" id="cb12-3" data-line-number="3">ab_official -&gt;<span class="st"> </span><span class="kw">atc_official</span>()</a>
<a class="sourceLine" id="cb12-4" data-line-number="4">ab_trivial_nl -&gt;<span class="st"> </span><span class="kw">atc_trivial_nl</span>()</a>
<a class="sourceLine" id="cb12-5" data-line-number="5">ab_certe -&gt;<span class="st"> </span><span class="kw">atc_certe</span>()</a>
<a class="sourceLine" id="cb12-6" data-line-number="6">ab_umcg -&gt;<span class="st"> </span><span class="kw">atc_umcg</span>()</a>
<a class="sourceLine" id="cb12-7" data-line-number="7">ab_tradenames -&gt;<span class="st"> </span><span class="kw">atc_tradenames</span>()</a></code></pre></div>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">ab_property -&gt;<span class="st"> </span><span class="kw">atc_property</span>()</a>
<a class="sourceLine" id="cb13-2" data-line-number="2">ab_name -&gt;<span class="st"> </span><span class="kw">atc_name</span>()</a>
<a class="sourceLine" id="cb13-3" data-line-number="3">ab_official -&gt;<span class="st"> </span><span class="kw">atc_official</span>()</a>
<a class="sourceLine" id="cb13-4" data-line-number="4">ab_trivial_nl -&gt;<span class="st"> </span><span class="kw">atc_trivial_nl</span>()</a>
<a class="sourceLine" id="cb13-5" data-line-number="5">ab_certe -&gt;<span class="st"> </span><span class="kw">atc_certe</span>()</a>
<a class="sourceLine" id="cb13-6" data-line-number="6">ab_umcg -&gt;<span class="st"> </span><span class="kw">atc_umcg</span>()</a>
<a class="sourceLine" id="cb13-7" data-line-number="7">ab_tradenames -&gt;<span class="st"> </span><span class="kw">atc_tradenames</span>()</a></code></pre></div>
These functions use <code>as.atc()</code> internally. The old <code>atc_property</code> has been renamed <code><a href="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
<li>New functions <code><a href="../reference/mo_source.html">set_mo_source()</a></code> and <code><a href="../reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><a href="../reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li>
<li>Support for the upcoming <a href="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
@ -696,20 +704,20 @@ These functions use <code>as.atc()</code> internally. The old <code>atc_property
<li>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
<li>
<p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://rdrr.io/r/graphics/plot.html">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(septic_patients, <span class="dt">col_ab =</span> <span class="st">"amox"</span>)</a>
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/graphics/plot.html">plot</a></span>(x)</a>
<a class="sourceLine" id="cb13-3" data-line-number="3"><span class="kw"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(x)</a></code></pre></div>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(septic_patients, <span class="dt">col_ab =</span> <span class="st">"amox"</span>)</a>
<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/r/graphics/plot.html">plot</a></span>(x)</a>
<a class="sourceLine" id="cb14-3" data-line-number="3"><span class="kw"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(x)</a></code></pre></div>
</li>
<li>
<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(...)</a>
<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="co"># or</span></a>
<a class="sourceLine" id="cb14-3" data-line-number="3"><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(septic_patients, ...)</a></code></pre></div>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(...)</a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="co"># or</span></a>
<a class="sourceLine" id="cb15-3" data-line-number="3"><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(septic_patients, ...)</a></code></pre></div>
<p>is equal to:</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
</li>
<li>New function <code><a href="../reference/availability.html">availability()</a></code> to check the number of available (non-empty) results in a <code>data.frame</code>
</li>
@ -738,33 +746,33 @@ These functions use <code>as.atc()</code> internally. The old <code>atc_property
<ul>
<li>
<p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1"><span class="co"># mo_fullname() uses as.mo() internally</span></a>
<a class="sourceLine" id="cb16-2" data-line-number="2"></a>
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Sthafilokockus aaureuz"</span>)</a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co">#&gt; [1] "Staphylococcus aureus"</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. klossi"</span>)</a>
<a class="sourceLine" id="cb16-7" data-line-number="7"><span class="co">#&gt; [1] "Staphylococcus kloosii"</span></a></code></pre></div>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1"><span class="co"># mo_fullname() uses as.mo() internally</span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"></a>
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Sthafilokockus aaureuz"</span>)</a>
<a class="sourceLine" id="cb17-4" data-line-number="4"><span class="co">#&gt; [1] "Staphylococcus aureus"</span></a>
<a class="sourceLine" id="cb17-5" data-line-number="5"></a>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. klossi"</span>)</a>
<a class="sourceLine" id="cb17-7" data-line-number="7"><span class="co">#&gt; [1] "Staphylococcus kloosii"</span></a></code></pre></div>
</li>
<li>
<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1"><span class="co"># equal:</span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">TRUE</span>)</a>
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb17-4" data-line-number="4"></a>
<a class="sourceLine" id="cb17-5" data-line-number="5"><span class="co"># also equal:</span></a>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb17-7" data-line-number="7"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">0</span>)</a></code></pre></div>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1"><span class="co"># equal:</span></a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">TRUE</span>)</a>
<a class="sourceLine" id="cb18-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb18-4" data-line-number="4"></a>
<a class="sourceLine" id="cb18-5" data-line-number="5"><span class="co"># also equal:</span></a>
<a class="sourceLine" id="cb18-6" data-line-number="6"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb18-7" data-line-number="7"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">0</span>)</a></code></pre></div>
Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a></code> could lead to very unreliable results.</li>
<li>Implemented the latest publication of Becker <em>et al.</em> (2019), for categorising coagulase-negative <em>Staphylococci</em>
</li>
<li>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</li>
<li>
<p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"qwerty"</span>, <span class="dt">language =</span> <span class="st">"es"</span>)</a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="co"># Warning: </span></a>
<a class="sourceLine" id="cb18-3" data-line-number="3"><span class="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span></a>
<a class="sourceLine" id="cb18-4" data-line-number="4"><span class="co">#&gt; [1] "(género desconocido)"</span></a></code></pre></div>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"qwerty"</span>, <span class="dt">language =</span> <span class="st">"es"</span>)</a>
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="co"># Warning: </span></a>
<a class="sourceLine" id="cb19-3" data-line-number="3"><span class="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span></a>
<a class="sourceLine" id="cb19-4" data-line-number="4"><span class="co">#&gt; [1] "(género desconocido)"</span></a></code></pre></div>
</li>
<li>Fix for vector containing only empty values</li>
<li>Finds better results when input is in other languages</li>
@ -810,19 +818,19 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<ul>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="co"># OLD WAY</span></a>
<a class="sourceLine" id="cb19-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(genus)</a>
<a class="sourceLine" id="cb19-6" data-line-number="6"><span class="co"># NEW WAY</span></a>
<a class="sourceLine" id="cb19-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a>
<a class="sourceLine" id="cb19-9" data-line-number="9"></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># Even supports grouping variables:</span></a>
<a class="sourceLine" id="cb19-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-12" data-line-number="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-13" data-line-number="13"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a></code></pre></div>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="co"># OLD WAY</span></a>
<a class="sourceLine" id="cb20-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb20-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb20-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(genus)</a>
<a class="sourceLine" id="cb20-6" data-line-number="6"><span class="co"># NEW WAY</span></a>
<a class="sourceLine" id="cb20-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a>
<a class="sourceLine" id="cb20-9" data-line-number="9"></a>
<a class="sourceLine" id="cb20-10" data-line-number="10"><span class="co"># Even supports grouping variables:</span></a>
<a class="sourceLine" id="cb20-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb20-12" data-line-number="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-13" data-line-number="13"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a></code></pre></div>
</li>
<li>Header info is now available as a list, with the <code>header</code> function</li>
<li>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</li>
@ -897,10 +905,10 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<li>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li>
<li>
<p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. species"</span>) <span class="co"># B_ESCHR</span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"E. spp."</span>) <span class="co"># "Escherichia species"</span></a>
<a class="sourceLine" id="cb20-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. spp"</span>) <span class="co"># B_STPHY</span></a>
<a class="sourceLine" id="cb20-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. species"</span>) <span class="co"># "Staphylococcus species"</span></a></code></pre></div>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. species"</span>) <span class="co"># B_ESCHR</span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"E. spp."</span>) <span class="co"># "Escherichia species"</span></a>
<a class="sourceLine" id="cb21-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. spp"</span>) <span class="co"># B_STPHY</span></a>
<a class="sourceLine" id="cb21-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. species"</span>) <span class="co"># "Staphylococcus species"</span></a></code></pre></div>
</li>
<li>Added parameter <code>combine_IR</code> (TRUE/FALSE) to functions <code>portion_df</code> and <code>count_df</code>, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</li>
<li>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</li>
@ -913,15 +921,15 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<ul>
<li>
<p>Support for grouping variables, test with:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(gender)</a></code></pre></div>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(gender)</a></code></pre></div>
</li>
<li>
<p>Support for (un)selecting columns:</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb23-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb23-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
</li>
<li>Check for <code><a href="https://rdrr.io/pkg/hms/man/Deprecated.html">hms::is.hms</a></code>
</li>
@ -1001,18 +1009,18 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
</ul>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb23-2" data-line-number="2"><span class="co"># [1] "Gram negative"</span></a>
<a class="sourceLine" id="cb23-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"de"</span>) <span class="co"># German</span></a>
<a class="sourceLine" id="cb23-4" data-line-number="4"><span class="co"># [1] "Gramnegativ"</span></a>
<a class="sourceLine" id="cb23-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># Spanish</span></a>
<a class="sourceLine" id="cb23-6" data-line-number="6"><span class="co"># [1] "Gram negativo"</span></a>
<a class="sourceLine" id="cb23-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. group A"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>) <span class="co"># Portuguese</span></a>
<a class="sourceLine" id="cb23-8" data-line-number="8"><span class="co"># [1] "Streptococcus grupo A"</span></a></code></pre></div>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb24-2" data-line-number="2"><span class="co"># [1] "Gram negative"</span></a>
<a class="sourceLine" id="cb24-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"de"</span>) <span class="co"># German</span></a>
<a class="sourceLine" id="cb24-4" data-line-number="4"><span class="co"># [1] "Gramnegativ"</span></a>
<a class="sourceLine" id="cb24-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># Spanish</span></a>
<a class="sourceLine" id="cb24-6" data-line-number="6"><span class="co"># [1] "Gram negativo"</span></a>
<a class="sourceLine" id="cb24-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. group A"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>) <span class="co"># Portuguese</span></a>
<a class="sourceLine" id="cb24-8" data-line-number="8"><span class="co"># [1] "Streptococcus grupo A"</span></a></code></pre></div>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"Esc blattae"</span>)</a>
<a class="sourceLine" id="cb24-2" data-line-number="2"><span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span></a>
<a class="sourceLine" id="cb24-3" data-line-number="3"><span class="co"># [1] "Gram negative"</span></a></code></pre></div>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"Esc blattae"</span>)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span></a>
<a class="sourceLine" id="cb25-3" data-line-number="3"><span class="co"># [1] "Gram negative"</span></a></code></pre></div>
</li>
<li>Functions <code>count_R</code>, <code>count_IR</code>, <code>count_I</code>, <code>count_SI</code> and <code>count_S</code> to selectively count resistant or susceptible isolates
<ul>
@ -1023,18 +1031,18 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using intelligent rules:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb25-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>)</a>
<a class="sourceLine" id="cb25-4" data-line-number="4"><span class="co"># [1] B_STPHY_AUR</span></a>
<a class="sourceLine" id="cb25-5" data-line-number="5"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S group A"</span>)</a>
<a class="sourceLine" id="cb25-6" data-line-number="6"><span class="co"># [1] B_STRPTC_GRA</span></a></code></pre></div>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="co"># [1] B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb26-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>)</a>
<a class="sourceLine" id="cb26-4" data-line-number="4"><span class="co"># [1] B_STPHY_AUR</span></a>
<a class="sourceLine" id="cb26-5" data-line-number="5"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S group A"</span>)</a>
<a class="sourceLine" id="cb26-6" data-line-number="6"><span class="co"># [1] B_STRPTC_GRA</span></a></code></pre></div>
<p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">thousands_of_E_colis &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/rep.html">rep</a></span>(<span class="st">"E. coli"</span>, <span class="dv">25000</span>)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2">microbenchmark<span class="op">::</span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(thousands_of_E_colis), <span class="dt">unit =</span> <span class="st">"s"</span>)</a>
<a class="sourceLine" id="cb26-3" data-line-number="3"><span class="co"># Unit: seconds</span></a>
<a class="sourceLine" id="cb26-4" data-line-number="4"><span class="co"># min median max neval</span></a>
<a class="sourceLine" id="cb26-5" data-line-number="5"><span class="co"># 0.01817717 0.01843957 0.03878077 100</span></a></code></pre></div>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1">thousands_of_E_colis &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/rep.html">rep</a></span>(<span class="st">"E. coli"</span>, <span class="dv">25000</span>)</a>
<a class="sourceLine" id="cb27-2" data-line-number="2">microbenchmark<span class="op">::</span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(thousands_of_E_colis), <span class="dt">unit =</span> <span class="st">"s"</span>)</a>
<a class="sourceLine" id="cb27-3" data-line-number="3"><span class="co"># Unit: seconds</span></a>
<a class="sourceLine" id="cb27-4" data-line-number="4"><span class="co"># min median max neval</span></a>
<a class="sourceLine" id="cb27-5" data-line-number="5"><span class="co"># 0.01817717 0.01843957 0.03878077 100</span></a></code></pre></div>
</li>
<li>Added parameter <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</li>
<li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:
@ -1062,12 +1070,12 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</li>
<li>
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1"><span class="kw">ab_official</span>(<span class="st">"Bactroban"</span>)</a>
<a class="sourceLine" id="cb27-2" data-line-number="2"><span class="co"># [1] "Mupirocin"</span></a>
<a class="sourceLine" id="cb27-3" data-line-number="3"><span class="kw"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb27-4" data-line-number="4"><span class="co"># [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"</span></a>
<a class="sourceLine" id="cb27-5" data-line-number="5"><span class="kw"><a href="../reference/ab_property.html">ab_atc</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb27-6" data-line-number="6"><span class="co"># [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</span></a></code></pre></div>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb28-1" data-line-number="1"><span class="kw">ab_official</span>(<span class="st">"Bactroban"</span>)</a>
<a class="sourceLine" id="cb28-2" data-line-number="2"><span class="co"># [1] "Mupirocin"</span></a>
<a class="sourceLine" id="cb28-3" data-line-number="3"><span class="kw"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb28-4" data-line-number="4"><span class="co"># [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"</span></a>
<a class="sourceLine" id="cb28-5" data-line-number="5"><span class="kw"><a href="../reference/ab_property.html">ab_atc</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb28-6" data-line-number="6"><span class="co"># [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</span></a></code></pre></div>
</li>
<li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li>
<li>Function <code>ratio</code> is now deprecated and will be removed in a future release, as it is not really the scope of this package</li>
@ -1078,13 +1086,13 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb28-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
<a class="sourceLine" id="cb28-2" data-line-number="2"><span class="co"># which is the same as:</span></a>
<a class="sourceLine" id="cb28-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>(amox, cipr)</a>
<a class="sourceLine" id="cb28-4" data-line-number="4"></a>
<a class="sourceLine" id="cb28-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/AMR-deprecated.html">portion_S</a></span>(amcl)</a>
<a class="sourceLine" id="cb28-6" data-line-number="6">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/AMR-deprecated.html">portion_S</a></span>(amcl, gent)</a>
<a class="sourceLine" id="cb28-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/AMR-deprecated.html">portion_S</a></span>(amcl, gent, pita)</a></code></pre></div>
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb29-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
<a class="sourceLine" id="cb29-2" data-line-number="2"><span class="co"># which is the same as:</span></a>
<a class="sourceLine" id="cb29-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>(amox, cipr)</a>
<a class="sourceLine" id="cb29-4" data-line-number="4"></a>
<a class="sourceLine" id="cb29-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/AMR-deprecated.html">portion_S</a></span>(amcl)</a>
<a class="sourceLine" id="cb29-6" data-line-number="6">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/AMR-deprecated.html">portion_S</a></span>(amcl, gent)</a>
<a class="sourceLine" id="cb29-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/AMR-deprecated.html">portion_S</a></span>(amcl, gent, pita)</a></code></pre></div>
</li>
<li>Edited <code>ggplot_rsi</code> and <code>geom_rsi</code> so they can cope with <code>count_df</code>. The new <code>fun</code> parameter has value <code>portion_df</code> at default, but can be set to <code>count_df</code>.</li>
<li>Fix for <code>ggplot_rsi</code> when the <code>ggplot2</code> package was not loaded</li>
@ -1098,12 +1106,12 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
</li>
<li>
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb29-1" data-line-number="1">my_matrix =<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/with.html">with</a></span>(septic_patients, <span class="kw"><a href="https://rdrr.io/r/base/matrix.html">matrix</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(age, gender), <span class="dt">ncol =</span> <span class="dv">2</span>))</a>
<a class="sourceLine" id="cb29-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(my_matrix)</a></code></pre></div>
<div class="sourceCode" id="cb30"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb30-1" data-line-number="1">my_matrix =<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/with.html">with</a></span>(septic_patients, <span class="kw"><a href="https://rdrr.io/r/base/matrix.html">matrix</a></span>(<span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(age, gender), <span class="dt">ncol =</span> <span class="dv">2</span>))</a>
<a class="sourceLine" id="cb30-2" data-line-number="2"><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(my_matrix)</a></code></pre></div>
<p>For lists, subsetting is possible:</p>
<div class="sourceCode" id="cb30"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb30-1" data-line-number="1">my_list =<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/list.html">list</a></span>(<span class="dt">age =</span> septic_patients<span class="op">$</span>age, <span class="dt">gender =</span> septic_patients<span class="op">$</span>gender)</a>
<a class="sourceLine" id="cb30-2" data-line-number="2">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(age)</a>
<a class="sourceLine" id="cb30-3" data-line-number="3">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(gender)</a></code></pre></div>
<div class="sourceCode" id="cb31"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb31-1" data-line-number="1">my_list =<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/list.html">list</a></span>(<span class="dt">age =</span> septic_patients<span class="op">$</span>age, <span class="dt">gender =</span> septic_patients<span class="op">$</span>gender)</a>
<a class="sourceLine" id="cb31-2" data-line-number="2">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(age)</a>
<a class="sourceLine" id="cb31-3" data-line-number="3">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(gender)</a></code></pre></div>
</li>
</ul>
</div>
@ -1337,7 +1345,7 @@ Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#amr-0-8-0-9029">0.8.0.9029</a></li>
<li><a href="#amr-0-8-0-9030">0.8.0.9030</a></li>
<li><a href="#amr-0-8-0">0.8.0</a></li>
<li><a href="#amr-0-7-1">0.7.1</a></li>
<li><a href="#amr-0-7-0">0.7.0</a></li>

2
docs/reference/AMR.html
View File

@ -85,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/reference/as.rsi.html
View File

@ -85,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/reference/count.html
View File

@ -86,7 +86,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/reference/index.html
View File

@ -84,7 +84,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/reference/mdro.html
View File

@ -85,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

2
docs/reference/proportion.html
View File

@ -86,7 +86,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>

18
docs/reference/resistance_predict.html
View File

@ -85,7 +85,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9027</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9030</span>
</span>
</div>
@ -289,7 +289,7 @@
</tr>
<tr>
<th>I_as_S</th>
<td><p>a logical to indicate whether values <code>I</code> should be treated as <code>S</code> (will otherwise be treated as <code>R</code>)</p></td>
<td><p>a logical to indicate whether values <code>I</code> should be treated as <code>S</code> (will otherwise be treated as <code>R</code>). The default, <code>TRUE</code>, follows the redefinition by EUCAST about the interpretion of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below.</p></td>
</tr>
<tr>
<th>preserve_measurements</th>
@ -332,6 +332,19 @@
<li><p><code>"lin"</code> or <code>"linear"</code>: a linear regression model</p></li>
</ul>
<h2 class="hasAnchor" id="interpretation-of-s-i-and-r"><a class="anchor" href="#interpretation-of-s-i-and-r"></a>Interpretation of S, I and R</h2>
<p>In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<ul>
<li><p><strong>S</strong> - Susceptible, standard dosing regimen: A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
<li><p><strong>I</strong> - Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
<li><p><strong>R</strong> - Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.</p></li>
</ul>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>This AMR package honours this new insight. Use <code><a href='proportion.html'>susceptibility</a>()</code> (equal to <code><a href='proportion.html'>proportion_SI</a>()</code>) to determine antimicrobial susceptibility and <code><a href='count.html'>count_susceptible</a>()</code> (equal to <code><a href='count.html'>count_SI</a>()</code>) to count susceptible isolates.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
@ -394,6 +407,7 @@
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#interpretation-of-s-i-and-r">Interpretation of S, I and R</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>

17
man/resistance_predict.Rd
View File

@ -38,7 +38,7 @@ ggplot_rsi_predict(x, main = paste("Resistance Prediction of", x_name),
\item{model}{the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using \code{\link{glm}(..., family = \link{binomial})}), assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See Details for all valid options.}
\item{I_as_S}{a logical to indicate whether values \code{I} should be treated as \code{S} (will otherwise be treated as \code{R})}
\item{I_as_S}{a logical to indicate whether values \code{I} should be treated as \code{S} (will otherwise be treated as \code{R}). The default, \code{TRUE}, follows the redefinition by EUCAST about the interpretion of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below.}
\item{preserve_measurements}{a logical to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.}
@ -74,6 +74,21 @@ Valid options for the statistical model are:
\item{\code{"lin"} or \code{"linear"}: a linear regression model}
}
}
\section{Interpretation of S, I and R}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I and R as shown below (\url{http://www.eucast.org/newsiandr/}). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".
\itemize{
\item{\strong{S} - }{Susceptible, standard dosing regimen: A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.}
\item{\strong{I} - }{Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.}
\item{\strong{R} - }{Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.}
}
Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
This AMR package honours this new insight. Use \code{\link{susceptibility}()} (equal to \code{\link{proportion_SI}()}) to determine antimicrobial susceptibility and \code{\link{count_susceptible}()} (equal to \code{\link{count_SI}()}) to count susceptible isolates.
}
\section{Read more on our website!}{
On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.

18
vignettes/AMR.Rmd
View File

@ -385,9 +385,10 @@ data_1st %>%
summarise("1. Amoxi/clav" = susceptibility(AMC),
"2. Gentamicin" = susceptibility(GEN),
"3. Amoxi/clav + genta" = susceptibility(AMC, GEN)) %>%
tidyr::gather("antibiotic", "S", -genus) %>%
# pivot_longer() from the tidyr package "lengthens" data:
tidyr::pivot_longer(-genus, names_to = "antibiotic") %>%
ggplot(aes(x = genus,
y = S,
y = value,
fill = antibiotic)) +
geom_col(position = "dodge2")
```
@ -463,14 +464,19 @@ The next example uses the included `example_isolates`, which is an anonymised da
We will compare the resistance to fosfomycin (column `FOS`) in hospital A and D. The input for the `fisher.test()` can be retrieved with a transformation like this:
```{r, results = 'markup'}
# use package 'tidyr' to pivot data;
# it gets installed with this 'AMR' package
library(tidyr)
check_FOS <- example_isolates %>%
filter(hospital_id %in% c("A", "D")) %>% # filter on only hospitals A and D
select(hospital_id, FOS) %>% # select the hospitals and fosfomycin
group_by(hospital_id) %>% # group on the hospitals
count_df(combine_SI = TRUE) %>% # count all isolates per group (hospital_id)
tidyr::spread(hospital_id, value) %>% # transform output so A and D are columns
select(A, D) %>% # and select these only
as.matrix() # transform to good old matrix for fisher.test()
pivot_wider(names_from = hospital_id, # transform output so A and D are columns
values_from = value) %>%
select(A, D) %>% # and only select these columns
as.matrix() # transform to a good old matrix for fisher.test()
check_FOS
```
@ -482,4 +488,4 @@ We can apply the test now with:
fisher.test(check_FOS)
```
As can be seen, the p value is `r round(fisher.test(check_FOS)$p.value, 3)`, which means that the fosfomycin resistances found in hospital A and D are really different.
As can be seen, the p value is `r round(fisher.test(check_FOS)$p.value, 3)`, which means that the fosfomycin resistance found in hospital A and D are really different.

2
vignettes/SPSS.Rmd
View File

@ -39,7 +39,7 @@ As said, SPSS is easier to learn than R. But SPSS, SAS and Stata come with major
* **R is extremely flexible.**
Because you write the syntax yourself, you can do anything you want. The flexibility in transforming, gathering, 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.
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.
* **R can be easily automated.**