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@ -6,15 +6,4 @@
|
||||
\description{
|
||||
These functions are so-called '\link{Deprecated}'. \strong{They will be removed in a future release.} Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
|
||||
}
|
||||
\section{Retired Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{retired}. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\keyword{internal}
|
||||
|
||||
@ -18,11 +18,6 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun
|
||||
\strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.} See \url{https://www.whocc.no/copyright_disclaimer/.}
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
as.ab("meropenem")
|
||||
ab_name("J01DH02")
|
||||
|
||||
@ -46,9 +46,7 @@ This example data set has the exact same structure as an export file from WHONET
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(WHONET)
|
||||
}
|
||||
|
||||
\keyword{datasets}
|
||||
|
||||
@ -57,19 +57,6 @@ With using \code{collapse}, this function will return a \link{character}:\cr
|
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\code{df \%>\% mutate(abx = ab_from_text(clinical_text, collapse = "|"))}
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# mind the bad spelling of amoxicillin in this line,
|
||||
# straight from a true health care record:
|
||||
|
||||
@ -95,14 +95,6 @@ The function \code{\link[=ab_url]{ab_url()}} will return the direct URL to the o
|
||||
|
||||
The function \code{\link[=set_ab_names]{set_ab_names()}} is a special column renaming function for \link{data.frame}s. It renames columns names that resemble antimicrobial drugs. It always makes sure that the new column names are unique. If \code{property = "atc"} is set, preference is given to ATC codes from the J-group.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Source}{
|
||||
|
||||
World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
|
||||
@ -115,11 +107,6 @@ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{htt
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# all properties:
|
||||
ab_name("AMX") # "Amoxicillin"
|
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@ -166,15 +153,18 @@ colnames(set_ab_names(example_isolates, NIT:VAN))
|
||||
\donttest{
|
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if (require("dplyr")) {
|
||||
example_isolates \%>\%
|
||||
set_ab_names()
|
||||
set_ab_names() \%>\%
|
||||
head()
|
||||
|
||||
# this does the same:
|
||||
example_isolates \%>\%
|
||||
rename_with(set_ab_names)
|
||||
rename_with(set_ab_names)\%>\%
|
||||
head()
|
||||
|
||||
# set_ab_names() works with any AB property:
|
||||
example_isolates \%>\%
|
||||
set_ab_names(property = "atc")
|
||||
set_ab_names(property = "atc")\%>\%
|
||||
head()
|
||||
|
||||
example_isolates \%>\%
|
||||
set_ab_names(where(is.rsi)) \%>\%
|
||||
|
||||
24
man/age.Rd
24
man/age.Rd
@ -21,34 +21,26 @@ age(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...)
|
||||
An \link{integer} (no decimals) if \code{exact = FALSE}, a \link{double} (with decimals) otherwise
|
||||
}
|
||||
\description{
|
||||
Calculates age in years based on a reference date, which is the sytem date at default.
|
||||
Calculates age in years based on a reference date, which is the system date at default.
|
||||
}
|
||||
\details{
|
||||
Ages below 0 will be returned as \code{NA} with a warning. Ages above 120 will only give a warning.
|
||||
|
||||
This function vectorises over both \code{x} and \code{reference}, meaning that either can have a length of 1 while the other argument has a larger length.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# 10 random birth dates
|
||||
df <- data.frame(birth_date = Sys.Date() - runif(10) * 25000)
|
||||
# 10 random pre-Y2K birth dates
|
||||
df <- data.frame(birth_date = as.Date("2000-01-01") - runif(10) * 25000)
|
||||
|
||||
# add ages
|
||||
df$age <- age(df$birth_date)
|
||||
|
||||
# add exact ages
|
||||
df$age_exact <- age(df$birth_date, exact = TRUE)
|
||||
|
||||
# add age at millenium switch
|
||||
df$age_at_y2k <- age(df$birth_date, "2000-01-01")
|
||||
|
||||
df
|
||||
}
|
||||
\seealso{
|
||||
|
||||
@ -33,19 +33,6 @@ The default is to split on young children (0-11), youth (12-24), young adults (2
|
||||
}
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
|
||||
|
||||
@ -64,7 +51,7 @@ age_groups(ages, 1:20 * 5)
|
||||
age_groups(ages, split_at = "fives")
|
||||
|
||||
# split specifically for children
|
||||
age_groups(ages, c(1, 2, 4, 6, 13, 17))
|
||||
age_groups(ages, c(1, 2, 4, 6, 13, 18))
|
||||
age_groups(ages, "children")
|
||||
|
||||
\donttest{
|
||||
@ -75,7 +62,10 @@ if (require("dplyr")) {
|
||||
filter(mo == as.mo("E. coli")) \%>\%
|
||||
group_by(age_group = age_groups(age)) \%>\%
|
||||
select(age_group, CIP) \%>\%
|
||||
ggplot_rsi(x = "age_group", minimum = 0)
|
||||
ggplot_rsi(x = "age_group",
|
||||
minimum = 0,
|
||||
x.title = "Age Group",
|
||||
title = "Ciprofloxacin resistance per age group")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -164,120 +164,109 @@ The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function c
|
||||
}
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Reference Data Publicly Available}{
|
||||
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
df <- example_isolates[ , c("hospital_id", "mo",
|
||||
"AMP", "AMC", "TZP", "CXM", "CRO", "GEN",
|
||||
"TOB", "COL", "IPM", "MEM", "TEC", "VAN")]
|
||||
|
||||
# base R ------------------------------------------------------------------
|
||||
|
||||
# select columns 'IPM' (imipenem) and 'MEM' (meropenem)
|
||||
example_isolates[, carbapenems()]
|
||||
df[, carbapenems()]
|
||||
|
||||
# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
|
||||
example_isolates[, c("mo", aminoglycosides())]
|
||||
df[, c("mo", aminoglycosides())]
|
||||
|
||||
# select only antibiotic columns with DDDs for oral treatment
|
||||
example_isolates[, administrable_per_os()]
|
||||
df[, administrable_per_os()]
|
||||
|
||||
# filter using any() or all()
|
||||
example_isolates[any(carbapenems() == "R"), ]
|
||||
subset(example_isolates, any(carbapenems() == "R"))
|
||||
df[any(carbapenems() == "R"), ]
|
||||
subset(df, any(carbapenems() == "R"))
|
||||
|
||||
# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
|
||||
example_isolates[any(carbapenems()), ]
|
||||
example_isolates[all(carbapenems()), ]
|
||||
df[any(carbapenems()), ]
|
||||
df[all(carbapenems()), ]
|
||||
|
||||
# filter with multiple antibiotic selectors using c()
|
||||
example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]
|
||||
df[all(c(carbapenems(), aminoglycosides()) == "R"), ]
|
||||
|
||||
# filter + select in one go: get penicillins in carbapenems-resistant strains
|
||||
example_isolates[any(carbapenems() == "R"), penicillins()]
|
||||
df[any(carbapenems() == "R"), penicillins()]
|
||||
|
||||
# You can combine selectors with '&' to be more specific. For example,
|
||||
# penicillins() would select benzylpenicillin ('peni G') and
|
||||
# administrable_per_os() would select erythromycin. Yet, when combined these
|
||||
# drugs are both omitted since benzylpenicillin is not administrable per os
|
||||
# and erythromycin is not a penicillin:
|
||||
example_isolates[, penicillins() & administrable_per_os()]
|
||||
df[, penicillins() & administrable_per_os()]
|
||||
|
||||
# ab_selector() applies a filter in the `antibiotics` data set and is thus very
|
||||
# flexible. For instance, to select antibiotic columns with an oral DDD of at
|
||||
# least 1 gram:
|
||||
example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
|
||||
df[, ab_selector(oral_ddd > 1 & oral_units == "g")]
|
||||
|
||||
# dplyr -------------------------------------------------------------------
|
||||
\donttest{
|
||||
if (require("dplyr")) {
|
||||
|
||||
# get AMR for all aminoglycosides e.g., per hospital:
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
summarise(across(aminoglycosides(), resistance))
|
||||
|
||||
# You can combine selectors with '&' to be more specific:
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
select(penicillins() & administrable_per_os())
|
||||
|
||||
# get AMR for only drugs that matter - no intrinsic resistance:
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
filter(mo_genus() \%in\% c("Escherichia", "Klebsiella")) \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
summarise(across(not_intrinsic_resistant(), resistance))
|
||||
|
||||
# get susceptibility for antibiotics whose name contains "trim":
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
filter(first_isolate()) \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
summarise(across(ab_selector(name \%like\% "trim"), susceptibility))
|
||||
|
||||
# this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
select(carbapenems())
|
||||
|
||||
# this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
select(mo, aminoglycosides())
|
||||
|
||||
# any() and all() work in dplyr's filter() too:
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
filter(any(aminoglycosides() == "R"),
|
||||
all(cephalosporins_2nd() == "R"))
|
||||
|
||||
# also works with c():
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
filter(any(c(carbapenems(), aminoglycosides()) == "R"))
|
||||
|
||||
# not setting any/all will automatically apply all():
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
filter(aminoglycosides() == "R")
|
||||
#> i Assuming a filter on all 4 aminoglycosides.
|
||||
|
||||
# this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
select(mo, ab_class("mycobact"))
|
||||
|
||||
# get bug/drug combinations for only macrolides in Gram-positives:
|
||||
example_isolates \%>\%
|
||||
# get bug/drug combinations for only glycopeptides in Gram-positives:
|
||||
df \%>\%
|
||||
filter(mo_is_gram_positive()) \%>\%
|
||||
select(mo, macrolides()) \%>\%
|
||||
select(mo, glycopeptides()) \%>\%
|
||||
bug_drug_combinations() \%>\%
|
||||
format()
|
||||
|
||||
@ -286,10 +275,12 @@ if (require("dplyr")) {
|
||||
select(penicillins()) # only the 'J01CA01' column will be selected
|
||||
|
||||
|
||||
# with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
|
||||
example_isolates[carbapenems() == "R", ]
|
||||
example_isolates \%>\% filter(carbapenems() == "R")
|
||||
example_isolates \%>\% filter(across(carbapenems(), ~.x == "R"))
|
||||
# with recent versions of dplyr this is all equal:
|
||||
x <- df[carbapenems() == "R", ]
|
||||
y <- df \%>\% filter(carbapenems() == "R")
|
||||
z <- df \%>\% filter(if_all(carbapenems(), ~.x == "R"))
|
||||
identical(x, y)
|
||||
identical(y, z)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -90,11 +90,10 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun
|
||||
\strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.} See \url{https://www.whocc.no/copyright_disclaimer/.}
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(antibiotics)
|
||||
head(antivirals)
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\link{microorganisms}, \link{intrinsic_resistant}
|
||||
}
|
||||
|
||||
13
man/as.ab.Rd
13
man/as.ab.Rd
@ -47,14 +47,6 @@ World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodo
|
||||
European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm}
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{WHOCC}{
|
||||
|
||||
\if{html}{\figure{logo_who.png}{options: height="60" style=margin-bottom:"5"} \cr}
|
||||
@ -72,11 +64,6 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# these examples all return "ERY", the ID of erythromycin:
|
||||
as.ab("J01FA01")
|
||||
|
||||
@ -33,39 +33,31 @@ Interpret disk values as RSI values with \code{\link[=as.rsi]{as.rsi()}}. It sup
|
||||
|
||||
\code{NA_disk_} is a missing value of the new \verb{<disk>} class.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
\donttest{
|
||||
# transform existing disk zones to the `disk` class
|
||||
df <- data.frame(microorganism = "E. coli",
|
||||
# transform existing disk zones to the `disk` class (using base R)
|
||||
df <- data.frame(microorganism = "Escherichia coli",
|
||||
AMP = 20,
|
||||
CIP = 14,
|
||||
GEN = 18,
|
||||
TOB = 16)
|
||||
df[, 2:5] <- lapply(df[, 2:5], as.disk)
|
||||
# same with dplyr:
|
||||
# df \%>\% mutate(across(AMP:TOB, as.disk))
|
||||
str(df)
|
||||
|
||||
#' \donttest{
|
||||
# transforming is easier with dplyr:
|
||||
if (require("dplyr")) {
|
||||
df \%>\% mutate(across(AMP:TOB, as.disk))
|
||||
}
|
||||
}
|
||||
|
||||
# interpret disk values, see ?as.rsi
|
||||
as.rsi(x = as.disk(18),
|
||||
mo = "Strep pneu", # `mo` will be coerced with as.mo()
|
||||
ab = "ampicillin", # and `ab` with as.ab()
|
||||
guideline = "EUCAST")
|
||||
|
||||
as.rsi(df)
|
||||
}
|
||||
|
||||
# interpret whole data set, pretend to be all from urinary tract infections:
|
||||
as.rsi(df, uti = TRUE)
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[=as.rsi]{as.rsi()}}
|
||||
|
||||
@ -77,44 +77,35 @@ Use \code{\link[=droplevels]{droplevels()}} to drop unused levels. At default, i
|
||||
|
||||
\code{NA_mic_} is a missing value of the new \verb{<mic>} class, analogous to e.g. base \R's \code{\link[base:NA]{NA_character_}}.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
|
||||
mic_data
|
||||
is.mic(mic_data)
|
||||
|
||||
# this can also coerce combined MIC/RSI values:
|
||||
as.mic("<=0.002; S") # will return <=0.002
|
||||
as.mic("<=0.002; S")
|
||||
|
||||
# mathematical processing treats MICs as [numeric] values
|
||||
# mathematical processing treats MICs as numeric values
|
||||
fivenum(mic_data)
|
||||
quantile(mic_data)
|
||||
all(mic_data < 512)
|
||||
|
||||
# interpret MIC values
|
||||
as.rsi(x = as.mic(2),
|
||||
mo = as.mo("S. pneumoniae"),
|
||||
mo = as.mo("Streptococcus pneumoniae"),
|
||||
ab = "AMX",
|
||||
guideline = "EUCAST")
|
||||
as.rsi(x = as.mic(4),
|
||||
mo = as.mo("S. pneumoniae"),
|
||||
as.rsi(x = as.mic(c(0.01, 2, 4, 8)),
|
||||
mo = as.mo("Streptococcus pneumoniae"),
|
||||
ab = "AMX",
|
||||
guideline = "EUCAST")
|
||||
|
||||
# plot MIC values, see ?plot
|
||||
plot(mic_data)
|
||||
plot(mic_data, mo = "E. coli", ab = "cipro")
|
||||
autoplot(mic_data, mo = "E. coli", ab = "cipro")
|
||||
autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
|
||||
autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "uk") # Ukrainian
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[=as.rsi]{as.rsi()}}
|
||||
|
||||
13
man/as.mo.Rd
13
man/as.mo.Rd
@ -138,14 +138,6 @@ The intelligent rules consider the prevalence of microorganisms in humans groupe
|
||||
}
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Matching Score for Microorganisms}{
|
||||
|
||||
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
|
||||
@ -184,11 +176,6 @@ This package contains the complete taxonomic tree of almost all microorganisms (
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
\donttest{
|
||||
# These examples all return "B_STPHY_AURS", the ID of S. aureus:
|
||||
|
||||
@ -154,32 +154,15 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
|
||||
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Reference Data Publicly Available}{
|
||||
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
example_isolates
|
||||
summary(example_isolates) # see all R/SI results at a glance
|
||||
\donttest{
|
||||
if (require("skimr")) {
|
||||
# class <rsi> supported in skim() too:
|
||||
skim(example_isolates)
|
||||
}
|
||||
}
|
||||
|
||||
# For INTERPRETING disk diffusion and MIC values -----------------------
|
||||
|
||||
# a whole data set, even with combined MIC values and disk zones
|
||||
|
||||
@ -69,19 +69,6 @@ Abbreviations of return values when using \code{property = "U"} (unit):
|
||||
|
||||
\strong{N.B. This function requires an internet connection and only works if the following packages are installed: \code{curl}, \code{rvest}, \code{xml2}.}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
\donttest{
|
||||
if (requireNamespace("curl") && requireNamespace("rvest") && requireNamespace("xml2")) {
|
||||
|
||||
@ -20,19 +20,6 @@ Easy check for data availability of all columns in a data set. This makes it eas
|
||||
\details{
|
||||
The function returns a \link{data.frame} with columns \code{"resistant"} and \code{"visual_resistance"}. The values in that columns are calculated with \code{\link[=resistance]{resistance()}}.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
availability(example_isolates)
|
||||
\donttest{
|
||||
|
||||
@ -63,23 +63,10 @@ Determine antimicrobial resistance (AMR) of all bug-drug combinations in your da
|
||||
\details{
|
||||
The function \code{\link[=format]{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.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
\donttest{
|
||||
x <- bug_drug_combinations(example_isolates)
|
||||
x
|
||||
head(x)
|
||||
format(x, translate_ab = "name (atc)")
|
||||
|
||||
# Use FUN to change to transformation of microorganism codes
|
||||
|
||||
@ -31,11 +31,6 @@ The Catalogue of Life (\url{http://www.catalogueoflife.org}) is the most compreh
|
||||
The syntax used to transform the original data to a cleansed \R format, can be found here: \url{https://github.com/msberends/AMR/blob/main/data-raw/reproduction_of_microorganisms.R}.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# Get version info of included data set
|
||||
catalogue_of_life_version()
|
||||
@ -43,28 +38,19 @@ catalogue_of_life_version()
|
||||
|
||||
# Get a note when a species was renamed
|
||||
mo_shortname("Chlamydophila psittaci")
|
||||
# Note: 'Chlamydophila psittaci' (Everett et al., 1999) was renamed back to
|
||||
# 'Chlamydia psittaci' (Page, 1968)
|
||||
#> [1] "C. psittaci"
|
||||
|
||||
# Get any property from the entire taxonomic tree for all included species
|
||||
mo_class("E. coli")
|
||||
#> [1] "Gammaproteobacteria"
|
||||
|
||||
mo_family("E. coli")
|
||||
#> [1] "Enterobacteriaceae"
|
||||
|
||||
mo_gramstain("E. coli") # based on kingdom and phylum, see ?mo_gramstain
|
||||
#> [1] "Gram-negative"
|
||||
|
||||
mo_ref("E. coli")
|
||||
#> [1] "Castellani et al., 1919"
|
||||
|
||||
# Do not get mistaken - this package is about microorganisms
|
||||
mo_kingdom("C. elegans")
|
||||
#> [1] "Fungi" # Fungi?!
|
||||
mo_name("C. elegans")
|
||||
#> [1] "Cladosporium elegans" # Because a microorganism was found
|
||||
}
|
||||
\seealso{
|
||||
Data set \link{microorganisms} for the actual data. \cr
|
||||
|
||||
@ -23,11 +23,6 @@ This package contains the complete taxonomic tree of almost all microorganisms (
|
||||
\link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\link{microorganisms}
|
||||
}
|
||||
|
||||
17
man/count.Rd
17
man/count.Rd
@ -72,14 +72,6 @@ The function \code{\link[=n_rsi]{n_rsi()}} is an alias of \code{\link[=count_all
|
||||
|
||||
The function \code{\link[=count_df]{count_df()}} takes any variable from \code{data} that has an \code{\link{rsi}} class (created with \code{\link[=as.rsi]{as.rsi()}}) and counts the number of S's, I's and R's. It also supports grouped variables. The function \code{\link[=rsi_df]{rsi_df()}} works exactly like \code{\link[=count_df]{count_df()}}, but adds the percentage of S, I and R.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Interpretation of R and S/I}{
|
||||
|
||||
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
|
||||
@ -132,15 +124,11 @@ and that, in combination therapies, for \code{only_all_tested = FALSE} applies t
|
||||
Using \code{only_all_tested} has no impact when only using one antibiotic as input.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# example_isolates is a data set available in the AMR package.
|
||||
?example_isolates
|
||||
# run ?example_isolates for more info.
|
||||
|
||||
# base R ------------------------------------------------------------
|
||||
count_resistant(example_isolates$AMX) # counts "R"
|
||||
count_susceptible(example_isolates$AMX) # counts "S" and "I"
|
||||
count_all(example_isolates$AMX) # counts "S", "I" and "R"
|
||||
@ -163,6 +151,7 @@ n_rsi(example_isolates$AMX)
|
||||
count_susceptible(example_isolates$AMX)
|
||||
susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
|
||||
|
||||
# dplyr -------------------------------------------------------------
|
||||
\donttest{
|
||||
if (require("dplyr")) {
|
||||
example_isolates \%>\%
|
||||
|
||||
@ -24,51 +24,51 @@ Some organisations have their own adoption of EUCAST rules. This function can be
|
||||
|
||||
If you are familiar with the \code{\link[dplyr:case_when]{case_when()}} function of the \code{dplyr} package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule itself is written \emph{before} the tilde (\code{~}) and the consequence of the rule is written \emph{after} the tilde:
|
||||
|
||||
\if{html}{\out{<div class="sourceCode">}}\preformatted{x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{x <- custom_eucast_rules(TZP == "S" ~ aminopenicillins == "S",
|
||||
TZP == "R" ~ aminopenicillins == "R")
|
||||
}\if{html}{\out{</div>}}
|
||||
|
||||
These are two custom EUCAST rules: if TZP (piperacillin/tazobactam) is "S", all aminopenicillins (ampicillin and amoxicillin) must be made "S", and if TZP is "R", aminopenicillins must be made "R". These rules can also be printed to the console, so it is immediately clear how they work:
|
||||
|
||||
\if{html}{\out{<div class="sourceCode">}}\preformatted{x
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{x
|
||||
#> A set of custom EUCAST rules:
|
||||
#>
|
||||
#> 1. If TZP is S then set to S:
|
||||
#> 1. If TZP is "S" then set to S :
|
||||
#> amoxicillin (AMX), ampicillin (AMP)
|
||||
#>
|
||||
#> 2. If TZP is R then set to R:
|
||||
#> 2. If TZP is "R" then set to R :
|
||||
#> amoxicillin (AMX), ampicillin (AMP)
|
||||
}\if{html}{\out{</div>}}
|
||||
|
||||
The rules (the part \emph{before} the tilde, in above example \code{TZP == "S"} and \code{TZP == "R"}) must be evaluable in your data set: it should be able to run as a filter in your data set without errors. This means for the above example that the column \code{TZP} must exist. We will create a sample data set and test the rules set:
|
||||
|
||||
\if{html}{\out{<div class="sourceCode">}}\preformatted{df <- data.frame(mo = c("E. coli", "K. pneumoniae"),
|
||||
TZP = "R",
|
||||
amox = "",
|
||||
AMP = "")
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{df <- data.frame(mo = c("Escherichia coli", "Klebsiella pneumoniae"),
|
||||
TZP = as.rsi("R"),
|
||||
ampi = as.rsi("S"),
|
||||
cipro = as.rsi("S"))
|
||||
df
|
||||
#> mo TZP amox AMP
|
||||
#> 1 E. coli R
|
||||
#> 2 K. pneumoniae R
|
||||
|
||||
eucast_rules(df, rules = "custom", custom_rules = x)
|
||||
#> mo TZP amox AMP
|
||||
#> 1 E. coli R R R
|
||||
#> 2 K. pneumoniae R R R
|
||||
#> mo TZP ampi cipro
|
||||
#> 1 Escherichia coli R S S
|
||||
#> 2 Klebsiella pneumoniae R S S
|
||||
|
||||
eucast_rules(df, rules = "custom", custom_rules = x, info = FALSE)
|
||||
#> mo TZP ampi cipro
|
||||
#> 1 Escherichia coli R R S
|
||||
#> 2 Klebsiella pneumoniae R R S
|
||||
}\if{html}{\out{</div>}}
|
||||
}
|
||||
|
||||
\subsection{Using taxonomic properties in rules}{
|
||||
|
||||
There is one exception in variables used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: mo, fullname, kingdom, phylum, class, order, family, genus, species, subspecies, rank, ref, species_id, source, prevalence and snomed. Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:
|
||||
There is one exception in variables used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: "mo", "fullname", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "species_id", "source", "prevalence" and "snomed". Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:
|
||||
|
||||
\if{html}{\out{<div class="sourceCode">}}\preformatted{y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
|
||||
TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")
|
||||
|
||||
eucast_rules(df, rules = "custom", custom_rules = y)
|
||||
#> mo TZP amox AMP
|
||||
#> 1 E. coli R
|
||||
#> 2 K. pneumoniae R R R
|
||||
eucast_rules(df, rules = "custom", custom_rules = y, info = FALSE)
|
||||
#> mo TZP ampi cipro
|
||||
#> 1 Escherichia coli R S S
|
||||
#> 2 Klebsiella pneumoniae R R S
|
||||
}\if{html}{\out{</div>}}
|
||||
}
|
||||
|
||||
@ -76,58 +76,49 @@ eucast_rules(df, rules = "custom", custom_rules = y)
|
||||
|
||||
It is possible to define antibiotic groups instead of single antibiotics for the rule consequence, the part \emph{after} the tilde. In above examples, the antibiotic group \code{aminopenicillins} is used to include ampicillin and amoxicillin. The following groups are allowed (case-insensitive). Within parentheses are the agents that will be matched when running the rule.
|
||||
\itemize{
|
||||
\item aminoglycosides\cr(amikacin, amikacin/fosfomycin, amphotericin B-high, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin and tobramycin-high)
|
||||
\item aminopenicillins\cr(amoxicillin and ampicillin)
|
||||
\item antifungals\cr(5-fluorocytosine, amphotericin B, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole and voriconazole)
|
||||
\item antimycobacterials\cr(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, morinamide, p-aminosalicylic acid, pretomanid, prothionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone/isoniazid, tiocarlide and viomycin)
|
||||
\item betalactams\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin and ticarcillin/clavulanic acid)
|
||||
\item carbapenems\cr(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil and tebipenem)
|
||||
\item cephalosporins\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
|
||||
\item cephalosporins_1st\cr(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin and cephradine)
|
||||
\item cephalosporins_2nd\cr(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil and loracarbef)
|
||||
\item cephalosporins_3rd\cr(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone and latamoxef)
|
||||
\item cephalosporins_4th\cr(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome and cefquinome)
|
||||
\item cephalosporins_5th\cr(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor and ceftolozane/tazobactam)
|
||||
\item cephalosporins_except_caz\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
|
||||
\item fluoroquinolones\cr(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
|
||||
\item glycopeptides\cr(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin and vancomycin-macromethod)
|
||||
\item glycopeptides_except_lipo\cr(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin and vancomycin-macromethod)
|
||||
\item lincosamides\cr(acetylmidecamycin, acetylspiramycin, clindamycin, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin and tylvalosin)
|
||||
\item lipoglycopeptides\cr(dalbavancin, oritavancin and telavancin)
|
||||
\item macrolides\cr(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin and tylvalosin)
|
||||
\item oxazolidinones\cr(cadazolid, cycloserine, linezolid, tedizolid and thiacetazone)
|
||||
\item penicillins\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin and ticarcillin/clavulanic acid)
|
||||
\item polymyxins\cr(colistin, polymyxin B and polymyxin B/polysorbate 80)
|
||||
\item quinolones\cr(besifloxacin, cinoxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
|
||||
\item streptogramins\cr(pristinamycin and quinupristin/dalfopristin)
|
||||
\item tetracyclines\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline and tigecycline)
|
||||
\item tetracyclines_except_tgc\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline and tetracycline)
|
||||
\item trimethoprims\cr(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim and trimethoprim/sulfamethoxazole)
|
||||
\item ureidopenicillins\cr(azlocillin, mezlocillin, piperacillin and piperacillin/tazobactam)
|
||||
\item "aminoglycosides"\cr(amikacin, amikacin/fosfomycin, amphotericin B-high, apramycin, arbekacin, astromicin, bekanamycin, dibekacin, framycetin, gentamicin, gentamicin-high, habekacin, hygromycin, isepamicin, kanamycin, kanamycin-high, kanamycin/cephalexin, micronomicin, neomycin, netilmicin, pentisomicin, plazomicin, propikacin, ribostamycin, sisomicin, streptoduocin, streptomycin, streptomycin-high, tobramycin and tobramycin-high)
|
||||
\item "aminopenicillins"\cr(amoxicillin and ampicillin)
|
||||
\item "antifungals"\cr(5-fluorocytosine, amphotericin B, anidulafungin, butoconazole, caspofungin, ciclopirox, clotrimazole, econazole, fluconazole, fosfluconazole, griseofulvin, hachimycin, ibrexafungerp, isavuconazole, isoconazole, itraconazole, ketoconazole, manogepix, micafungin, miconazole, nystatin, pimaricin, posaconazole, rezafungin, ribociclib, sulconazole, terbinafine, terconazole and voriconazole)
|
||||
\item "antimycobacterials"\cr(4-aminosalicylic acid, calcium aminosalicylate, capreomycin, clofazimine, delamanid, enviomycin, ethambutol, ethambutol/isoniazid, ethionamide, isoniazid, morinamide, p-aminosalicylic acid, pretomanid, prothionamide, pyrazinamide, rifabutin, rifampicin, rifampicin/isoniazid, rifampicin/pyrazinamide/ethambutol/isoniazid, rifampicin/pyrazinamide/isoniazid, rifamycin, rifapentine, simvastatin/fenofibrate, sodium aminosalicylate, streptomycin/isoniazid, terizidone, thioacetazone/isoniazid, tiocarlide and viomycin)
|
||||
\item "betalactams"\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, biapenem, carbenicillin, carindacillin, cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/nacubactam, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, ciclacillin, clometocillin, cloxacillin, dicloxacillin, doripenem, epicillin, ertapenem, flucloxacillin, hetacillin, imipenem, imipenem/EDTA, imipenem/relebactam, latamoxef, lenampicillin, loracarbef, mecillinam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, panipenem, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, razupenem, ritipenem, ritipenem acoxil, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, tebipenem, temocillin, ticarcillin and ticarcillin/clavulanic acid)
|
||||
\item "carbapenems"\cr(biapenem, doripenem, ertapenem, imipenem, imipenem/EDTA, imipenem/relebactam, meropenem, meropenem/nacubactam, meropenem/vaborbactam, panipenem, razupenem, ritipenem, ritipenem acoxil and tebipenem)
|
||||
\item "cephalosporins"\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
|
||||
\item "cephalosporins_1st"\cr(cefacetrile, cefadroxil, cefaloridine, cefatrizine, cefazedone, cefazolin, cefroxadine, ceftezole, cephalexin, cephalothin, cephapirin and cephradine)
|
||||
\item "cephalosporins_2nd"\cr(cefaclor, cefamandole, cefmetazole, cefonicid, ceforanide, cefotetan, cefotiam, cefoxitin, cefoxitin screening, cefprozil, cefuroxime, cefuroxime axetil and loracarbef)
|
||||
\item "cephalosporins_3rd"\cr(cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefetamet, cefetamet pivoxil, cefixime, cefmenoxime, cefodizime, cefoperazone, cefoperazone/sulbactam, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotiam hexetil, cefovecin, cefpimizole, cefpiramide, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefsulodin, ceftazidime, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftriaxone and latamoxef)
|
||||
\item "cephalosporins_4th"\cr(cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetecol, cefoselis, cefozopran, cefpirome and cefquinome)
|
||||
\item "cephalosporins_5th"\cr(ceftaroline, ceftaroline/avibactam, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor and ceftolozane/tazobactam)
|
||||
\item "cephalosporins_except_caz"\cr(cefacetrile, cefaclor, cefadroxil, cefaloridine, cefamandole, cefatrizine, cefazedone, cefazolin, cefcapene, cefcapene pivoxil, cefdinir, cefditoren, cefditoren pivoxil, cefepime, cefepime/clavulanic acid, cefepime/tazobactam, cefetamet, cefetamet pivoxil, cefetecol, cefetrizole, cefixime, cefmenoxime, cefmetazole, cefodizime, cefonicid, cefoperazone, cefoperazone/sulbactam, ceforanide, cefoselis, cefotaxime, cefotaxime/clavulanic acid, cefotaxime/sulbactam, cefotetan, cefotiam, cefotiam hexetil, cefovecin, cefoxitin, cefoxitin screening, cefozopran, cefpimizole, cefpiramide, cefpirome, cefpodoxime, cefpodoxime proxetil, cefpodoxime/clavulanic acid, cefprozil, cefquinome, cefroxadine, cefsulodin, cefsumide, ceftaroline, ceftaroline/avibactam, ceftazidime/avibactam, ceftazidime/clavulanic acid, cefteram, cefteram pivoxil, ceftezole, ceftibuten, ceftiofur, ceftizoxime, ceftizoxime alapivoxil, ceftobiprole, ceftobiprole medocaril, ceftolozane/enzyme inhibitor, ceftolozane/tazobactam, ceftriaxone, cefuroxime, cefuroxime axetil, cephalexin, cephalothin, cephapirin, cephradine, latamoxef and loracarbef)
|
||||
\item "fluoroquinolones"\cr(besifloxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nifuroquine, norfloxacin, ofloxacin, orbifloxacin, pazufloxacin, pefloxacin, pradofloxacin, premafloxacin, prulifloxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
|
||||
\item "glycopeptides"\cr(avoparcin, dalbavancin, norvancomycin, oritavancin, ramoplanin, teicoplanin, teicoplanin-macromethod, telavancin, vancomycin and vancomycin-macromethod)
|
||||
\item "glycopeptides_except_lipo"\cr(avoparcin, norvancomycin, ramoplanin, teicoplanin, teicoplanin-macromethod, vancomycin and vancomycin-macromethod)
|
||||
\item "lincosamides"\cr(acetylmidecamycin, acetylspiramycin, clindamycin, gamithromycin, kitasamycin, lincomycin, meleumycin, nafithromycin, pirlimycin, primycin, solithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin and tylvalosin)
|
||||
\item "lipoglycopeptides"\cr(dalbavancin, oritavancin and telavancin)
|
||||
\item "macrolides"\cr(acetylmidecamycin, acetylspiramycin, azithromycin, clarithromycin, dirithromycin, erythromycin, flurithromycin, gamithromycin, josamycin, kitasamycin, meleumycin, midecamycin, miocamycin, nafithromycin, oleandomycin, pirlimycin, primycin, rokitamycin, roxithromycin, solithromycin, spiramycin, telithromycin, tildipirosin, tilmicosin, troleandomycin, tulathromycin, tylosin and tylvalosin)
|
||||
\item "oxazolidinones"\cr(cadazolid, cycloserine, linezolid, tedizolid and thiacetazone)
|
||||
\item "penicillins"\cr(amoxicillin, amoxicillin/clavulanic acid, amoxicillin/sulbactam, ampicillin, ampicillin/sulbactam, apalcillin, aspoxicillin, avibactam, azidocillin, azlocillin, aztreonam, aztreonam/avibactam, aztreonam/nacubactam, bacampicillin, benzathine benzylpenicillin, benzathine phenoxymethylpenicillin, benzylpenicillin, carbenicillin, carindacillin, cefepime/nacubactam, ciclacillin, clometocillin, cloxacillin, dicloxacillin, epicillin, flucloxacillin, hetacillin, lenampicillin, mecillinam, metampicillin, methicillin, mezlocillin, mezlocillin/sulbactam, nacubactam, nafcillin, oxacillin, penamecillin, penicillin/novobiocin, penicillin/sulbactam, phenethicillin, phenoxymethylpenicillin, piperacillin, piperacillin/sulbactam, piperacillin/tazobactam, piridicillin, pivampicillin, pivmecillinam, procaine benzylpenicillin, propicillin, sarmoxicillin, sulbactam, sulbenicillin, sultamicillin, talampicillin, tazobactam, temocillin, ticarcillin and ticarcillin/clavulanic acid)
|
||||
\item "polymyxins"\cr(colistin, polymyxin B and polymyxin B/polysorbate 80)
|
||||
\item "quinolones"\cr(besifloxacin, cinoxacin, ciprofloxacin, clinafloxacin, danofloxacin, delafloxacin, difloxacin, enoxacin, enrofloxacin, finafloxacin, fleroxacin, flumequine, garenoxacin, gatifloxacin, gemifloxacin, grepafloxacin, levofloxacin, levonadifloxacin, lomefloxacin, marbofloxacin, metioxate, miloxacin, moxifloxacin, nadifloxacin, nalidixic acid, nifuroquine, nitroxoline, norfloxacin, ofloxacin, orbifloxacin, oxolinic acid, pazufloxacin, pefloxacin, pipemidic acid, piromidic acid, pradofloxacin, premafloxacin, prulifloxacin, rosoxacin, rufloxacin, sarafloxacin, sitafloxacin, sparfloxacin, temafloxacin, tilbroquinol, tioxacin, tosufloxacin and trovafloxacin)
|
||||
\item "streptogramins"\cr(pristinamycin and quinupristin/dalfopristin)
|
||||
\item "tetracyclines"\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline, tetracycline and tigecycline)
|
||||
\item "tetracyclines_except_tgc"\cr(cetocycline, chlortetracycline, clomocycline, demeclocycline, doxycycline, eravacycline, lymecycline, metacycline, minocycline, omadacycline, oxytetracycline, penimepicycline, rolitetracycline and tetracycline)
|
||||
\item "trimethoprims"\cr(brodimoprim, sulfadiazine, sulfadiazine/tetroxoprim, sulfadiazine/trimethoprim, sulfadimethoxine, sulfadimidine, sulfadimidine/trimethoprim, sulfafurazole, sulfaisodimidine, sulfalene, sulfamazone, sulfamerazine, sulfamerazine/trimethoprim, sulfamethizole, sulfamethoxazole, sulfamethoxypyridazine, sulfametomidine, sulfametoxydiazine, sulfametrole/trimethoprim, sulfamoxole, sulfamoxole/trimethoprim, sulfanilamide, sulfaperin, sulfaphenazole, sulfapyridine, sulfathiazole, sulfathiourea, trimethoprim and trimethoprim/sulfamethoxazole)
|
||||
\item "ureidopenicillins"\cr(azlocillin, mezlocillin, piperacillin and piperacillin/tazobactam)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
x <- custom_eucast_rules(AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
|
||||
AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I")
|
||||
x
|
||||
|
||||
# run the custom rule set (verbose = TRUE will return a logbook instead of the data set):
|
||||
eucast_rules(example_isolates,
|
||||
rules = "custom",
|
||||
custom_rules = x,
|
||||
info = FALSE)
|
||||
info = FALSE,
|
||||
verbose = TRUE)
|
||||
|
||||
# combine rule sets
|
||||
x2 <- c(x,
|
||||
|
||||
@ -32,9 +32,7 @@ EUCAST breakpoints used in this package are based on the dosages in this data se
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(dosage)
|
||||
}
|
||||
|
||||
\keyword{datasets}
|
||||
|
||||
File diff suppressed because one or more lines are too long
@ -30,9 +30,7 @@ A data set containing 2,000 microbial isolates with their full antibiograms. The
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(example_isolates)
|
||||
}
|
||||
|
||||
\keyword{datasets}
|
||||
|
||||
@ -25,9 +25,7 @@ A data set containing 3,000 microbial isolates that are not cleaned up and conse
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(example_isolates_unclean)
|
||||
}
|
||||
|
||||
\keyword{datasets}
|
||||
|
||||
@ -1 +0,0 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="112" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="112" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#e05d44" d="M55 0h57v20H55z"/><path fill="url(#b)" d="M0 0h112v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="825" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="470">archived</text><text x="825" y="140" transform="scale(.1)" textLength="470">archived</text></g> </svg>
|
||||
|
Before Width: | Height: | Size: 967 B |
@ -1 +0,0 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="112" height="20"><linearGradient id="b" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="a"><rect width="112" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#a)"><path fill="#555" d="M0 0h55v20H0z"/><path fill="#007ec6" d="M55 0h57v20H55z"/><path fill="url(#b)" d="M0 0h112v20H0z"/></g><g fill="#fff" text-anchor="middle" font-family="DejaVu Sans,Verdana,Geneva,sans-serif" font-size="110"> <text x="285" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="450">lifecycle</text><text x="285" y="140" transform="scale(.1)" textLength="450">lifecycle</text><text x="825" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="470">dormant</text><text x="825" y="140" transform="scale(.1)" textLength="470">dormant</text></g> </svg>
|
||||
|
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|
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|
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|
Before Width: | Height: | Size: 973 B |
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|
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|
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|
Before Width: | Height: | Size: 957 B |
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||||
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<style>
|
||||
text {
|
||||
fill: white;
|
||||
font-family: "Helvetica Neue";
|
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}
|
||||
</style>
|
||||
<defs>
|
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<marker id="a" color="black" overflow="visible" markerHeight="6" markerWidth="7" orient="auto" viewBox="-1 -3 7 6">
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</marker>
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</defs>
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<g fill="none">
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<title>Canvas 1</title>
|
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<rect width="510.24" height="184.25" fill="#fff"/>
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<g>
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<title>Layer 1</title>
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<text transform="translate(447.875 143.1545)" dominant-baseline="middle" text-anchor="middle">superseded</text>
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|
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</g>
|
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</g>
|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 1.9 KiB |
@ -164,19 +164,6 @@ The default method is phenotype-based (using \code{type = "points"}) and episode
|
||||
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
@ -184,7 +171,7 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
|
||||
example_isolates[first_isolate(), ]
|
||||
\donttest{
|
||||
# get all first Gram-negatives
|
||||
example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
|
||||
example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ]
|
||||
|
||||
if (require("dplyr")) {
|
||||
# filter on first isolates using dplyr:
|
||||
@ -193,12 +180,13 @@ if (require("dplyr")) {
|
||||
|
||||
# short-hand version:
|
||||
example_isolates \%>\%
|
||||
filter_first_isolate()
|
||||
filter_first_isolate(info = FALSE)
|
||||
|
||||
# grouped determination of first isolates (also prints group names):
|
||||
# flag the first isolates per group:
|
||||
example_isolates \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
mutate(first = first_isolate())
|
||||
mutate(first = first_isolate()) \%>\%
|
||||
select(hospital_id, date, patient_id, mo, first)
|
||||
|
||||
# now let's see if first isolates matter:
|
||||
A <- example_isolates \%>\%
|
||||
@ -213,6 +201,9 @@ if (require("dplyr")) {
|
||||
resistance = resistance(GEN)) # gentamicin resistance
|
||||
|
||||
# Have a look at A and B.
|
||||
A
|
||||
B
|
||||
|
||||
# B is more reliable because every isolate is counted only once.
|
||||
# Gentamicin resistance in hospital D appears to be 4.2\% higher than
|
||||
# when you (erroneously) would have used all isolates for analysis.
|
||||
|
||||
@ -99,17 +99,6 @@ where \code{df} are the degrees of freedom.
|
||||
If there are more than two categories and you want to find out which ones are significantly different from their null expectation, you can use the same method of testing each category vs. the sum of all categories, with the Bonferroni correction. You use \emph{G}-tests for each category, of course.
|
||||
}
|
||||
}
|
||||
\section{Questioning Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_questioning.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{questioning}. This function might be no longer be optimal approach, or is it questionable whether this function should be in this \code{AMR} package at all.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# = EXAMPLE 1 =
|
||||
# Shivrain et al. (2006) crossed clearfield rice (which are resistant
|
||||
@ -121,8 +110,7 @@ On our website \url{https://msberends.github.io/AMR/} you can find \href{https:/
|
||||
# ratio.
|
||||
|
||||
x <- c(772, 1611, 737)
|
||||
G <- g.test(x, p = c(1, 2, 1) / 4)
|
||||
# G$p.value = 0.12574.
|
||||
g.test(x, p = c(1, 2, 1) / 4)
|
||||
|
||||
# There is no significant difference from a 1:2:1 ratio.
|
||||
# Meaning: resistance controlled by a single gene with two co-dominant
|
||||
@ -138,11 +126,9 @@ G <- g.test(x, p = c(1, 2, 1) / 4)
|
||||
|
||||
x <- c(1752, 1895)
|
||||
g.test(x)
|
||||
# p = 0.01787343
|
||||
|
||||
# There is a significant difference from a 1:1 ratio.
|
||||
# Meaning: there are significantly more left-billed birds.
|
||||
|
||||
}
|
||||
\references{
|
||||
\enumerate{
|
||||
|
||||
@ -32,28 +32,16 @@ The \code{\link[=first_isolate]{first_isolate()}} function is a wrapper around t
|
||||
|
||||
The \code{dplyr} package is not required for these functions to work, but these functions do support \link[dplyr:group_by]{variable grouping} and work conveniently inside \code{dplyr} verbs such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
# See ?example_isolates
|
||||
df <- example_isolates[sample(seq_len(2000), size = 200), ]
|
||||
|
||||
get_episode(example_isolates$date, episode_days = 60) # indices
|
||||
is_new_episode(example_isolates$date, episode_days = 60) # TRUE/FALSE
|
||||
get_episode(df$date, episode_days = 60) # indices
|
||||
is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
|
||||
|
||||
# filter on results from the third 60-day episode only, using base R
|
||||
example_isolates[which(get_episode(example_isolates$date, 60) == 3), ]
|
||||
df[which(get_episode(df$date, 60) == 3), ]
|
||||
|
||||
# the functions also work for less than a day, e.g. to include one per hour:
|
||||
get_episode(c(Sys.time(),
|
||||
@ -64,24 +52,24 @@ get_episode(c(Sys.time(),
|
||||
if (require("dplyr")) {
|
||||
# is_new_episode() can also be used in dplyr verbs to determine patient
|
||||
# episodes based on any (combination of) grouping variables:
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
mutate(condition = sample(x = c("A", "B", "C"),
|
||||
size = 2000,
|
||||
replace = TRUE)) \%>\%
|
||||
group_by(condition) \%>\%
|
||||
mutate(new_episode = is_new_episode(date, 365))
|
||||
mutate(new_episode = is_new_episode(date, 365)) \%>\%
|
||||
select(patient_id, date, condition, new_episode)
|
||||
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
group_by(hospital_id, patient_id) \%>\%
|
||||
transmute(date,
|
||||
patient_id,
|
||||
new_index = get_episode(date, 60),
|
||||
new_logical = is_new_episode(date, 60))
|
||||
|
||||
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
summarise(patients = n_distinct(patient_id),
|
||||
summarise(n_patients = n_distinct(patient_id),
|
||||
n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
|
||||
n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
|
||||
n_episodes_30 = sum(is_new_episode(date, episode_days = 30)))
|
||||
@ -89,21 +77,23 @@ if (require("dplyr")) {
|
||||
|
||||
# grouping on patients and microorganisms leads to the same
|
||||
# results as first_isolate() when using 'episode-based':
|
||||
x <- example_isolates \%>\%
|
||||
x <- df \%>\%
|
||||
filter_first_isolate(include_unknown = TRUE,
|
||||
method = "episode-based")
|
||||
|
||||
y <- example_isolates \%>\%
|
||||
y <- df \%>\%
|
||||
group_by(patient_id, mo) \%>\%
|
||||
filter(is_new_episode(date, 365))
|
||||
filter(is_new_episode(date, 365)) \%>\%
|
||||
ungroup()
|
||||
|
||||
identical(x$patient_id, y$patient_id)
|
||||
identical(x, y)
|
||||
|
||||
# but is_new_episode() has a lot more flexibility than first_isolate(),
|
||||
# since you can now group on anything that seems relevant:
|
||||
example_isolates \%>\%
|
||||
df \%>\%
|
||||
group_by(patient_id, mo, hospital_id, ward_icu) \%>\%
|
||||
mutate(flag_episode = is_new_episode(date, 365))
|
||||
mutate(flag_episode = is_new_episode(date, 365)) \%>\%
|
||||
select(group_vars(.), flag_episode)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -108,35 +108,32 @@ Produces a \code{ggplot2} variant of a so-called \href{https://en.wikipedia.org/
|
||||
\details{
|
||||
The colours for labels and points can be changed by adding another scale layer for colour, such as \code{scale_colour_viridis_d()} and \code{scale_colour_brewer()}.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
|
||||
# See ?pca for more info about Principal Component Analysis (PCA).
|
||||
\donttest{
|
||||
if (require("dplyr")) {
|
||||
pca_model <- example_isolates \%>\%
|
||||
filter(mo_genus(mo) == "Staphylococcus") \%>\%
|
||||
group_by(species = mo_shortname(mo)) \%>\%
|
||||
summarise_if (is.rsi, resistance) \%>\%
|
||||
pca(FLC, AMC, CXM, GEN, TOB, TMP, SXT, CIP, TEC, TCY, ERY)
|
||||
# calculate the resistance per group first
|
||||
resistance_data <- example_isolates \%>\%
|
||||
group_by(order = mo_order(mo), # group on anything, like order
|
||||
genus = mo_genus(mo)) \%>\% # and genus as we do here;
|
||||
filter(n() >= 30) \%>\% # filter on only 30 results per group
|
||||
summarise_if(is.rsi, resistance) # then get resistance of all drugs
|
||||
|
||||
# old (base R)
|
||||
biplot(pca_model)
|
||||
# now conduct PCA for certain antimicrobial agents
|
||||
pca_result <- resistance_data \%>\%
|
||||
pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, SXT)
|
||||
|
||||
summary(pca_result)
|
||||
|
||||
# new
|
||||
ggplot_pca(pca_model)
|
||||
# old base R plotting method:
|
||||
biplot(pca_result)
|
||||
# new ggplot2 plotting method using this package:
|
||||
ggplot_pca(pca_result)
|
||||
|
||||
if (require("ggplot2")) {
|
||||
ggplot_pca(pca_model) +
|
||||
ggplot_pca(pca_result) +
|
||||
scale_colour_viridis_d() +
|
||||
labs(title = "Title here")
|
||||
}
|
||||
|
||||
@ -140,19 +140,6 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin
|
||||
\code{\link[=ggplot_rsi]{ggplot_rsi()}} is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (\verb{\%>\%}). See \emph{Examples}.
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
\donttest{
|
||||
if (require("ggplot2") & require("dplyr")) {
|
||||
|
||||
@ -29,19 +29,6 @@ This tries to find a column name in a data set based on information from the \li
|
||||
\details{
|
||||
You can look for an antibiotic (trade) name or abbreviation and it will search \code{x} and the \link{antibiotics} data set for any column containing a name or code of that antibiotic. \strong{Longer columns names take precedence over shorter column names.}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
df <- data.frame(amox = "S",
|
||||
tetr = "R")
|
||||
|
||||
@ -27,21 +27,7 @@ This data set is based on \href{https://www.eucast.org/expert_rules_and_expected
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
\donttest{
|
||||
if (require("dplyr")) {
|
||||
intrinsic_resistant \%>\%
|
||||
mutate(mo = mo_name(mo),
|
||||
ab = ab_name(mo))
|
||||
filter(ab == "Vancomycin" & mo \%like\% "Enterococcus") \%>\%
|
||||
pull(mo)
|
||||
#> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum"
|
||||
}
|
||||
}
|
||||
head(intrinsic_resistant)
|
||||
}
|
||||
\keyword{datasets}
|
||||
|
||||
@ -15,7 +15,7 @@ italicize_taxonomy(string, type = c("markdown", "ansi"))
|
||||
\item{type}{type of conversion of the taxonomic names, either "markdown" or "ansi", see \emph{Details}}
|
||||
}
|
||||
\description{
|
||||
According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
|
||||
According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italics. This function finds taxonomic names within strings and makes them italic.
|
||||
}
|
||||
\details{
|
||||
This function finds the taxonomic names and makes them italic based on the \link{microorganisms} data set.
|
||||
@ -24,32 +24,9 @@ The taxonomic names can be italicised using markdown (the default) by adding \co
|
||||
|
||||
This function also supports abbreviation of the genus if it is followed by a species, such as "E. coli" and "K. pneumoniae ozaenae".
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
italicise_taxonomy("An overview of Staphylococcus aureus isolates")
|
||||
italicise_taxonomy("An overview of S. aureus isolates")
|
||||
|
||||
cat(italicise_taxonomy("An overview of S. aureus isolates", type = "ansi"))
|
||||
|
||||
# since ggplot2 supports no markdown (yet), use
|
||||
# italicise_taxonomy() and the `ggtext` package for titles:
|
||||
\donttest{
|
||||
if (require("ggplot2") && require("ggtext")) {
|
||||
autoplot(example_isolates$AMC,
|
||||
title = italicise_taxonomy("Amoxi/clav in E. coli")) +
|
||||
theme(plot.title = ggtext::element_markdown())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
13
man/join.Rd
13
man/join.Rd
@ -43,19 +43,6 @@ Join the data set \link{microorganisms} easily to an existing data set or to a \
|
||||
|
||||
If the \code{dplyr} package is installed, their join functions will be used. Otherwise, the much slower \code{\link[=merge]{merge()}} and \code{\link[=interaction]{interaction()}} functions from base \R will be used.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
left_join_microorganisms(as.mo("K. pneumoniae"))
|
||||
left_join_microorganisms("B_KLBSL_PNMN")
|
||||
|
||||
@ -107,19 +107,6 @@ The default antimicrobial agents used for \strong{fungi} (set in \code{antifunga
|
||||
\item Voriconazole
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
@ -147,7 +134,7 @@ if (require("dplyr")) {
|
||||
first_weighted = first_isolate(col_keyantimicrobials = "keyab")
|
||||
)
|
||||
|
||||
# Check the difference, in this data set it results in more isolates:
|
||||
# Check the difference in this data set, 'weighted' results in more isolates:
|
||||
sum(my_patients$first_regular, na.rm = TRUE)
|
||||
sum(my_patients$first_weighted, na.rm = TRUE)
|
||||
}
|
||||
|
||||
@ -25,19 +25,10 @@ kurtosis(x, na.rm = FALSE, excess = FALSE)
|
||||
\description{
|
||||
Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
\examples{
|
||||
kurtosis(rnorm(10000))
|
||||
kurtosis(rnorm(10000), excess = TRUE)
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\code{\link[=skewness]{skewness()}}
|
||||
}
|
||||
|
||||
@ -1,43 +0,0 @@
|
||||
% Generated by roxygen2: do not edit by hand
|
||||
% Please edit documentation in R/lifecycle.R
|
||||
\name{lifecycle}
|
||||
\alias{lifecycle}
|
||||
\title{Lifecycles of Functions in the \code{AMR} Package}
|
||||
\description{
|
||||
Functions in this \code{AMR} package are categorised using \href{https://lifecycle.r-lib.org/articles/stages.html}{the lifecycle circle of the Tidyverse as found on www.tidyverse.org/lifecycle}.
|
||||
|
||||
\if{html}{\figure{lifecycle_tidyverse.svg}{options: height="200" style=margin-bottom:"5"} \cr}
|
||||
This page contains a section for every lifecycle (with text borrowed from the aforementioned Tidyverse website), so they can be used in the manual pages of the functions.
|
||||
}
|
||||
\section{Experimental Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_experimental.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{experimental}. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this \code{AMR} package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.
|
||||
}
|
||||
|
||||
\section{Maturing Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Retired Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{retired}. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.
|
||||
}
|
||||
|
||||
\section{Questioning Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_questioning.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{questioning}. This function might be no longer be optimal approach, or is it questionable whether this function should be in this \code{AMR} package at all.
|
||||
}
|
||||
|
||||
19
man/like.Rd
19
man/like.Rd
@ -45,39 +45,20 @@ These \code{\link[=like]{like()}} and \verb{\%like\%}/\verb{\%unlike\%} function
|
||||
|
||||
Using RStudio? The \verb{\%like\%}/\verb{\%unlike\%} functions can also be directly inserted in your code from the Addins menu and can have its own keyboard shortcut like \code{Shift+Ctrl+L} or \code{Shift+Cmd+L} (see menu \code{Tools} > \verb{Modify Keyboard Shortcuts...}). If you keep pressing your shortcut, the inserted text will be iterated over \verb{\%like\%} -> \verb{\%unlike\%} -> \verb{\%like_case\%} -> \verb{\%unlike_case\%}.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
a <- "This is a test"
|
||||
b <- "TEST"
|
||||
a \%like\% b
|
||||
#> TRUE
|
||||
b \%like\% a
|
||||
#> FALSE
|
||||
|
||||
# also supports multiple patterns
|
||||
a <- c("Test case", "Something different", "Yet another thing")
|
||||
b <- c( "case", "diff", "yet")
|
||||
a \%like\% b
|
||||
#> TRUE TRUE TRUE
|
||||
a \%unlike\% b
|
||||
#> FALSE FALSE FALSE
|
||||
|
||||
a[1] \%like\% b
|
||||
#> TRUE FALSE FALSE
|
||||
a \%like\% b[1]
|
||||
#> TRUE FALSE FALSE
|
||||
|
||||
# get isolates whose name start with 'Ent' or 'ent'
|
||||
example_isolates[which(mo_name(example_isolates$mo) \%like\% "^ent"), ]
|
||||
|
||||
32
man/mdro.Rd
32
man/mdro.Rd
@ -163,14 +163,6 @@ table(x)
|
||||
The rules set (the \code{custom} object in this case) could be exported to a shared file location using \code{\link[=saveRDS]{saveRDS()}} if you collaborate with multiple users. The custom rules set could then be imported using \code{\link[=readRDS]{readRDS()}}.
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Antibiotics}{
|
||||
|
||||
To define antibiotics column names, leave as it is to determine it automatically with \code{\link[=guess_ab_col]{guess_ab_col()}} or input a text (case-insensitive), or use \code{NULL} to skip a column (e.g. \code{TIC = NULL} to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
|
||||
@ -195,17 +187,15 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
|
||||
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
mdro(example_isolates, guideline = "EUCAST")
|
||||
out <- mdro(example_isolates, guideline = "EUCAST")
|
||||
str(out)
|
||||
table(out)
|
||||
|
||||
mdro(example_isolates,
|
||||
guideline = custom_mdro_guideline(AMX == "R" ~ "Custom MDRO 1",
|
||||
VAN == "R" ~ "Custom MDRO 2"))
|
||||
out <- mdro(example_isolates,
|
||||
guideline = custom_mdro_guideline(AMX == "R" ~ "Custom MDRO 1",
|
||||
VAN == "R" ~ "Custom MDRO 2"))
|
||||
table(out)
|
||||
|
||||
\donttest{
|
||||
if (require("dplyr")) {
|
||||
@ -215,10 +205,10 @@ if (require("dplyr")) {
|
||||
|
||||
# no need to define `x` when used inside dplyr verbs:
|
||||
example_isolates \%>\%
|
||||
mutate(MDRO = mdro(),
|
||||
EUCAST = eucast_exceptional_phenotypes(),
|
||||
BRMO = brmo(),
|
||||
MRGN = mrgn())
|
||||
mutate(MDRO = mdro()) \%>\%
|
||||
pull(MDRO) \%>\%
|
||||
table()
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -90,11 +90,9 @@ This package contains the complete taxonomic tree of almost all microorganisms (
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(microorganisms)
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\code{\link[=as.mo]{as.mo()}}, \code{\link[=mo_property]{mo_property()}}, \link{microorganisms.codes}, \link{intrinsic_resistant}
|
||||
}
|
||||
|
||||
@ -30,11 +30,9 @@ This package contains the complete taxonomic tree of almost all microorganisms (
|
||||
\link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which versions of the CoL and LPSN were included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(microorganisms.codes)
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\code{\link[=as.mo]{as.mo()}} \link{microorganisms}
|
||||
}
|
||||
|
||||
@ -37,11 +37,9 @@ This package contains the complete taxonomic tree of almost all microorganisms (
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(microorganisms.old)
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\code{\link[=as.mo]{as.mo()}} \code{\link[=mo_property]{mo_property()}} \link{microorganisms}
|
||||
}
|
||||
|
||||
@ -39,24 +39,11 @@ All matches are sorted descending on their matching score and for all user input
|
||||
Since \code{AMR} version 1.8.1, common microorganism abbreviations are ignored in determining the matching score. These abbreviations are currently: AIEC, ATEC, BORSA, CRSM, DAEC, EAEC, EHEC, EIEC, EPEC, ETEC, GISA, MRPA, MRSA, MRSE, MSSA, MSSE, NMEC, PISP, PRSP, STEC, UPEC, VISA, VISP, VRE, VRSA and VRSP.
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Reference Data Publicly Available}{
|
||||
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
as.mo("E. coli")
|
||||
mo_uncertainties()
|
||||
|
||||
@ -139,14 +139,6 @@ The function \code{\link[=mo_url]{mo_url()}} will return the direct URL to the o
|
||||
|
||||
SNOMED codes - \code{\link[=mo_snomed]{mo_snomed()}} - are from the US Edition of SNOMED CT from 1 September 2020. See \emph{Source} and the \link{microorganisms} data set for more info.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Matching Score for Microorganisms}{
|
||||
|
||||
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
|
||||
@ -198,97 +190,91 @@ This package contains the complete taxonomic tree of almost all microorganisms (
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# taxonomic tree -----------------------------------------------------------
|
||||
mo_kingdom("E. coli") # "Bacteria"
|
||||
mo_phylum("E. coli") # "Proteobacteria"
|
||||
mo_class("E. coli") # "Gammaproteobacteria"
|
||||
mo_order("E. coli") # "Enterobacterales"
|
||||
mo_family("E. coli") # "Enterobacteriaceae"
|
||||
mo_genus("E. coli") # "Escherichia"
|
||||
mo_species("E. coli") # "coli"
|
||||
mo_subspecies("E. coli") # ""
|
||||
mo_kingdom("Klebsiella pneumoniae")
|
||||
mo_phylum("Klebsiella pneumoniae")
|
||||
mo_class("Klebsiella pneumoniae")
|
||||
mo_order("Klebsiella pneumoniae")
|
||||
mo_family("Klebsiella pneumoniae")
|
||||
mo_genus("Klebsiella pneumoniae")
|
||||
mo_species("Klebsiella pneumoniae")
|
||||
mo_subspecies("Klebsiella pneumoniae")
|
||||
|
||||
# colloquial properties ----------------------------------------------------
|
||||
mo_name("E. coli") # "Escherichia coli"
|
||||
mo_fullname("E. coli") # "Escherichia coli" - same as mo_name()
|
||||
mo_shortname("E. coli") # "E. coli"
|
||||
mo_name("Klebsiella pneumoniae")
|
||||
mo_fullname("Klebsiella pneumoniae")
|
||||
mo_shortname("Klebsiella pneumoniae")
|
||||
|
||||
# other properties ---------------------------------------------------------
|
||||
mo_gramstain("E. coli") # "Gram-negative"
|
||||
mo_snomed("E. coli") # 112283007, 116395006, ... (SNOMED codes)
|
||||
mo_type("E. coli") # "Bacteria" (equal to kingdom, but may be translated)
|
||||
mo_rank("E. coli") # "species"
|
||||
mo_url("E. coli") # get the direct url to the online database entry
|
||||
mo_synonyms("E. coli") # get previously accepted taxonomic names
|
||||
mo_gramstain("Klebsiella pneumoniae")
|
||||
mo_snomed("Klebsiella pneumoniae")
|
||||
mo_type("Klebsiella pneumoniae")
|
||||
mo_rank("Klebsiella pneumoniae")
|
||||
mo_url("Klebsiella pneumoniae")
|
||||
mo_synonyms("Klebsiella pneumoniae")
|
||||
|
||||
# scientific reference -----------------------------------------------------
|
||||
mo_ref("E. coli") # "Castellani et al., 1919"
|
||||
mo_authors("E. coli") # "Castellani et al."
|
||||
mo_year("E. coli") # 1919
|
||||
mo_lpsn("E. coli") # 776057 (LPSN record ID)
|
||||
mo_ref("Klebsiella pneumoniae")
|
||||
mo_authors("Klebsiella pneumoniae")
|
||||
mo_year("Klebsiella pneumoniae")
|
||||
mo_lpsn("Klebsiella pneumoniae")
|
||||
|
||||
# abbreviations known in the field -----------------------------------------
|
||||
mo_genus("MRSA") # "Staphylococcus"
|
||||
mo_species("MRSA") # "aureus"
|
||||
mo_shortname("VISA") # "S. aureus"
|
||||
mo_gramstain("VISA") # "Gram-positive"
|
||||
mo_genus("MRSA")
|
||||
mo_species("MRSA")
|
||||
mo_shortname("VISA")
|
||||
mo_gramstain("VISA")
|
||||
|
||||
mo_genus("EHEC") # "Escherichia"
|
||||
mo_species("EHEC") # "coli"
|
||||
mo_genus("EHEC")
|
||||
mo_species("EHEC")
|
||||
|
||||
# known subspecies ---------------------------------------------------------
|
||||
mo_name("doylei") # "Campylobacter jejuni doylei"
|
||||
mo_genus("doylei") # "Campylobacter"
|
||||
mo_species("doylei") # "jejuni"
|
||||
mo_subspecies("doylei") # "doylei"
|
||||
mo_name("doylei")
|
||||
mo_genus("doylei")
|
||||
mo_species("doylei")
|
||||
mo_subspecies("doylei")
|
||||
|
||||
mo_fullname("K. pneu rh") # "Klebsiella pneumoniae rhinoscleromatis"
|
||||
mo_shortname("K. pneu rh") # "K. pneumoniae"
|
||||
mo_fullname("K. pneu rh")
|
||||
mo_shortname("K. pneu rh")
|
||||
|
||||
\donttest{
|
||||
# Becker classification, see ?as.mo ----------------------------------------
|
||||
mo_fullname("S. epi") # "Staphylococcus epidermidis"
|
||||
mo_fullname("S. epi", Becker = TRUE) # "Coagulase-negative Staphylococcus (CoNS)"
|
||||
mo_shortname("S. epi") # "S. epidermidis"
|
||||
mo_shortname("S. epi", Becker = TRUE) # "CoNS"
|
||||
mo_fullname("S. epi")
|
||||
mo_fullname("S. epi", Becker = TRUE)
|
||||
mo_shortname("S. epi")
|
||||
mo_shortname("S. epi", Becker = TRUE)
|
||||
|
||||
# Lancefield classification, see ?as.mo ------------------------------------
|
||||
mo_fullname("S. pyo") # "Streptococcus pyogenes"
|
||||
mo_fullname("S. pyo", Lancefield = TRUE) # "Streptococcus group A"
|
||||
mo_shortname("S. pyo") # "S. pyogenes"
|
||||
mo_shortname("S. pyo", Lancefield = TRUE) # "GAS" (='Group A Streptococci')
|
||||
mo_fullname("S. pyo")
|
||||
mo_fullname("S. pyo", Lancefield = TRUE)
|
||||
mo_shortname("S. pyo")
|
||||
mo_shortname("S. pyo", Lancefield = TRUE)
|
||||
|
||||
|
||||
# language support --------------------------------------------------------
|
||||
mo_gramstain("E. coli", language = "de") # "Gramnegativ"
|
||||
mo_gramstain("E. coli", language = "nl") # "Gram-negatief"
|
||||
mo_gramstain("E. coli", language = "es") # "Gram negativo"
|
||||
mo_gramstain("Klebsiella pneumoniae", language = "de")
|
||||
mo_gramstain("Klebsiella pneumoniae", language = "nl")
|
||||
mo_gramstain("Klebsiella pneumoniae", language = "es")
|
||||
|
||||
# mo_type is equal to mo_kingdom, but mo_kingdom will remain official
|
||||
mo_kingdom("E. coli") # "Bacteria" on a German system
|
||||
mo_type("E. coli") # "Bakterien" on a German system
|
||||
mo_type("E. coli") # "Bacteria" on an English system
|
||||
mo_kingdom("Klebsiella pneumoniae")
|
||||
mo_type("Klebsiella pneumoniae")
|
||||
mo_type("Klebsiella pneumoniae")
|
||||
|
||||
mo_fullname("S. pyogenes",
|
||||
Lancefield = TRUE,
|
||||
language = "de") # "Streptococcus Gruppe A"
|
||||
language = "de")
|
||||
mo_fullname("S. pyogenes",
|
||||
Lancefield = TRUE,
|
||||
language = "nl") # "Streptococcus groep A"
|
||||
language = "nl")
|
||||
|
||||
|
||||
# other --------------------------------------------------------------------
|
||||
|
||||
mo_is_yeast(c("Candida", "E. coli")) # TRUE, FALSE
|
||||
mo_is_yeast(c("Candida", "Trichophyton", "Klebsiella"))
|
||||
|
||||
# gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
|
||||
\donttest{
|
||||
# gram stains and intrinsic resistance can be used as a filter in dplyr verbs
|
||||
if (require("dplyr")) {
|
||||
example_isolates \%>\%
|
||||
filter(mo_is_gram_positive())
|
||||
@ -299,11 +285,11 @@ if (require("dplyr")) {
|
||||
|
||||
|
||||
# get a list with the complete taxonomy (from kingdom to subspecies)
|
||||
mo_taxonomy("E. coli")
|
||||
mo_taxonomy("Klebsiella pneumoniae")
|
||||
|
||||
# get a list with the taxonomy, the authors, Gram-stain,
|
||||
# SNOMED codes, and URL to the online database
|
||||
mo_info("E. coli")
|
||||
}
|
||||
# SNOMED codes, and URL to the online database
|
||||
mo_info("Klebsiella pneumoniae")
|
||||
}
|
||||
}
|
||||
\seealso{
|
||||
|
||||
@ -107,16 +107,3 @@ To delete the reference data file, just use \code{""}, \code{NULL} or \code{FALS
|
||||
If the original file (in the previous case an Excel file) is moved or deleted, the \code{mo_source.rds} file will be removed upon the next use of \code{\link[=as.mo]{as.mo()}} or any \code{\link[=mo_property]{mo_*}} function.
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
|
||||
25
man/pca.Rd
25
man/pca.Rd
@ -59,19 +59,6 @@ The \code{\link[=pca]{pca()}} function takes a \link{data.frame} as input and pe
|
||||
|
||||
The result of the \code{\link[=pca]{pca()}} function is a \link{prcomp} object, with an additional attribute \code{non_numeric_cols} which is a vector with the column names of all columns that do not contain \link{numeric} values. These are probably the groups and labels, and will be used by \code{\link[=ggplot_pca]{ggplot_pca()}}.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# `example_isolates` is a data set available in the AMR package.
|
||||
# See ?example_isolates.
|
||||
@ -82,6 +69,7 @@ if (require("dplyr")) {
|
||||
resistance_data <- example_isolates \%>\%
|
||||
group_by(order = mo_order(mo), # group on anything, like order
|
||||
genus = mo_genus(mo)) \%>\% # and genus as we do here;
|
||||
filter(n() >= 30) \%>\% # filter on only 30 results per group
|
||||
summarise_if(is.rsi, resistance) # then get resistance of all drugs
|
||||
|
||||
# now conduct PCA for certain antimicrobial agents
|
||||
@ -90,8 +78,17 @@ if (require("dplyr")) {
|
||||
|
||||
pca_result
|
||||
summary(pca_result)
|
||||
|
||||
# old base R plotting method:
|
||||
biplot(pca_result)
|
||||
ggplot_pca(pca_result) # a new and convenient plot function
|
||||
# new ggplot2 plotting method using this package:
|
||||
ggplot_pca(pca_result)
|
||||
|
||||
if (require("ggplot2")) {
|
||||
ggplot_pca(pca_result) +
|
||||
scale_colour_viridis_d() +
|
||||
labs(title = "Title here")
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
13
man/plot.Rd
13
man/plot.Rd
@ -130,19 +130,6 @@ For interpreting MIC values as well as disk diffusion diameters, supported guide
|
||||
|
||||
Simply using \code{"CLSI"} or \code{"EUCAST"} as input will automatically select the latest version of that guideline.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
some_mic_values <- random_mic(size = 100)
|
||||
some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
|
||||
|
||||
@ -124,14 +124,6 @@ and that, in combination therapies, for \code{only_all_tested = FALSE} applies t
|
||||
Using \code{only_all_tested} has no impact when only using one antibiotic as input.
|
||||
}
|
||||
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Interpretation of R and S/I}{
|
||||
|
||||
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
|
||||
@ -147,15 +139,11 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
|
||||
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# example_isolates is a data set available in the AMR package.
|
||||
?example_isolates
|
||||
# run ?example_isolates for more info.
|
||||
|
||||
# base R ------------------------------------------------------------
|
||||
resistance(example_isolates$AMX) # determines \%R
|
||||
susceptibility(example_isolates$AMX) # determines \%S+I
|
||||
|
||||
@ -166,6 +154,7 @@ proportion_I(example_isolates$AMX)
|
||||
proportion_IR(example_isolates$AMX)
|
||||
proportion_R(example_isolates$AMX)
|
||||
|
||||
# dplyr -------------------------------------------------------------
|
||||
\donttest{
|
||||
if (require("dplyr")) {
|
||||
example_isolates \%>\%
|
||||
@ -220,10 +209,11 @@ if (require("dplyr")) {
|
||||
proportion_df(translate = FALSE)
|
||||
|
||||
# It also supports grouping variables
|
||||
# (use rsi_df to also include the count)
|
||||
example_isolates \%>\%
|
||||
select(hospital_id, AMX, CIP) \%>\%
|
||||
group_by(hospital_id) \%>\%
|
||||
proportion_df(translate = FALSE)
|
||||
rsi_df(translate = FALSE)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -35,32 +35,19 @@ The base \R function \code{\link[=sample]{sample()}} is used for generating valu
|
||||
|
||||
Generated values are based on the EUCAST 2022 guideline as implemented in the \link{rsi_translation} data set. To create specific generated values per bug or drug, set the \code{mo} and/or \code{ab} argument.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
random_mic(100)
|
||||
random_disk(100)
|
||||
random_rsi(100)
|
||||
random_mic(25)
|
||||
random_disk(25)
|
||||
random_rsi(25)
|
||||
|
||||
\donttest{
|
||||
# make the random generation more realistic by setting a bug and/or drug:
|
||||
random_mic(100, "Klebsiella pneumoniae") # range 0.0625-64
|
||||
random_mic(100, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
|
||||
random_mic(100, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
|
||||
random_mic(25, "Klebsiella pneumoniae") # range 0.0625-64
|
||||
random_mic(25, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16
|
||||
random_mic(25, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4
|
||||
|
||||
random_disk(100, "Klebsiella pneumoniae") # range 8-50
|
||||
random_disk(100, "Klebsiella pneumoniae", "ampicillin") # range 11-17
|
||||
random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 12-27
|
||||
random_disk(25, "Klebsiella pneumoniae") # range 8-50
|
||||
random_disk(25, "Klebsiella pneumoniae", "ampicillin") # range 11-17
|
||||
random_disk(25, "Streptococcus pneumoniae", "ampicillin") # range 12-27
|
||||
}
|
||||
}
|
||||
|
||||
@ -110,14 +110,6 @@ Valid options for the statistical model (argument \code{model}) are:
|
||||
\item \code{"lin"} or \code{"linear"}: a linear regression model
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Interpretation of R and S/I}{
|
||||
|
||||
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
|
||||
@ -133,11 +125,6 @@ A microorganism is categorised as \emph{Susceptible, Increased exposure} when th
|
||||
This AMR package honours this (new) insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
x <- resistance_predict(example_isolates,
|
||||
col_ab = "AMX",
|
||||
@ -172,24 +159,8 @@ if (require("dplyr") & require("ggplot2")) {
|
||||
model = "binomial",
|
||||
info = FALSE,
|
||||
minimum = 15)
|
||||
|
||||
head(data)
|
||||
autoplot(data)
|
||||
|
||||
ggplot(data,
|
||||
aes(x = year)) +
|
||||
geom_col(aes(y = value),
|
||||
fill = "grey75") +
|
||||
geom_errorbar(aes(ymin = se_min,
|
||||
ymax = se_max),
|
||||
colour = "grey50") +
|
||||
scale_y_continuous(limits = c(0, 1),
|
||||
breaks = seq(0, 1, 0.1),
|
||||
labels = paste0(seq(0, 100, 10), "\%")) +
|
||||
labs(title = expression(paste("Forecast of Amoxicillin Resistance in ",
|
||||
italic("E. coli"))),
|
||||
y = "\%R",
|
||||
x = "Year") +
|
||||
theme_minimal(base_size = 13)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -27,25 +27,6 @@ rsi_translation
|
||||
Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2022) and CLSI (2011-2022). Use \code{\link[=as.rsi]{as.rsi()}} to transform MICs or disks measurements to R/SI values.
|
||||
}
|
||||
\details{
|
||||
Overview of the data set:
|
||||
|
||||
\if{html}{\out{<div class="sourceCode r">}}\preformatted{head(rsi_translation)
|
||||
#> guideline method site mo rank_index ab ref_tbl disk_dose
|
||||
#> 1 EUCAST 2022 MIC <NA> F_ASPRG_MGTS 2 AMB Aspergillus <NA>
|
||||
#> 2 EUCAST 2022 MIC <NA> F_ASPRG_NIGR 2 AMB Aspergillus <NA>
|
||||
#> 3 EUCAST 2022 MIC <NA> F_CANDD 3 AMB Candida <NA>
|
||||
#> 4 EUCAST 2022 MIC <NA> F_CANDD_ALBC 2 AMB Candida <NA>
|
||||
#> 5 EUCAST 2022 MIC <NA> F_CANDD_DBLN 2 AMB Candida <NA>
|
||||
#> 6 EUCAST 2022 MIC <NA> F_CANDD_KRUS 2 AMB Candida <NA>
|
||||
#> breakpoint_S breakpoint_R uti
|
||||
#> 1 1 1 FALSE
|
||||
#> 2 1 1 FALSE
|
||||
#> 3 1 1 FALSE
|
||||
#> 4 1 1 FALSE
|
||||
#> 5 1 1 FALSE
|
||||
#> 6 1 1 FALSE
|
||||
}\if{html}{\out{</div>}}
|
||||
|
||||
The repository of this \code{AMR} package contains a file comprising this exact data set: \url{https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt}. This file \strong{allows for machine reading EUCAST and CLSI guidelines}, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the \code{mo} and \code{ab} columns have been transformed to contain the full official names instead of codes.
|
||||
}
|
||||
\section{Reference Data Publicly Available}{
|
||||
@ -53,11 +34,9 @@ The repository of this \code{AMR} package contains a file comprising this exact
|
||||
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
\examples{
|
||||
head(rsi_translation)
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\link{intrinsic_resistant}
|
||||
}
|
||||
|
||||
@ -25,19 +25,9 @@ Skewness is a measure of the asymmetry of the probability distribution of a real
|
||||
|
||||
When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
\examples{
|
||||
skewness(runif(1000))
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\seealso{
|
||||
\code{\link[=kurtosis]{kurtosis()}}
|
||||
}
|
||||
|
||||
@ -27,7 +27,7 @@ For language-dependent output of AMR functions, like \code{\link[=mo_name]{mo_na
|
||||
\details{
|
||||
The currently 16 supported languages are English, Chinese, Danish, Dutch, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish and Ukrainian. All these languages have translations available for all antimicrobial agents and colloquial microorganism names.
|
||||
|
||||
Please read about adding or updating a language in \href{https://github.com/msberends/AMR/blob/main/developer-guideline.md}{our developer guideline}.
|
||||
Please read about adding or updating a language in \href{https://github.com/msberends/AMR/wiki/}{our Wiki}.
|
||||
\subsection{Changing the Default Language}{
|
||||
|
||||
The system language will be used at default (as returned by \code{Sys.getenv("LANG")} or, if \code{LANG} is not set, \link{Sys.getlocale("LC_COLLATE")}), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
|
||||
@ -41,19 +41,6 @@ Note that setting an \R option only works in the same session. Save the command
|
||||
Thus, if the R option \code{AMR_locale} is set, the system variables \code{LANGUAGE} and \code{LANG} will be ignored.
|
||||
}
|
||||
}
|
||||
\section{Stable Lifecycle}{
|
||||
|
||||
\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
|
||||
The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
|
||||
|
||||
If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
|
||||
}
|
||||
|
||||
\section{Read more on Our Website!}{
|
||||
|
||||
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
|
||||
}
|
||||
|
||||
\examples{
|
||||
# Current settings (based on system language)
|
||||
ab_name("Ciprofloxacin")
|
||||
|
||||
Reference in New Issue
Block a user