diff --git a/DESCRIPTION b/DESCRIPTION
index d9a94b3d..4ff2a0b7 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: AMR
-Version: 0.8.0.9033
-Date: 2019-11-18
+Version: 0.8.0.9034
+Date: 2019-11-23
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),
diff --git a/NEWS.md b/NEWS.md
index e8825b6b..1c63f884 100755
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,5 @@
-# AMR 0.8.0.9033
-## Last updated: 18-Nov-2019
+# AMR 0.8.0.9034
+## Last updated: 23-Nov-2019
### Breaking
* Adopted Adeolu *et al.* (2016), [PMID 27620848](https://www.ncbi.nlm.nih.gov/pubmed/27620848) for the `microorganisms` data set, which means that the new order Enterobacterales now consists of a part of the existing family Enterobacteriaceae, but that this family has been split into other families as well (like *Morganellaceae* and *Yersiniaceae*). Although published in 2016, this information is not yet in the Catalogue of Life version of 2019. All MDRO determinations with `mdro()` will now use the Enterobacterales order for all guidelines before 2016 that were dependent on the Enterobacteriaceae family.
diff --git a/R/data.R b/R/data.R
index f1fbb0a7..c7551b13 100755
--- a/R/data.R
+++ b/R/data.R
@@ -19,10 +19,11 @@
# Visit our website for more info: https://msberends.gitlab.io/AMR. #
# ==================================================================== #
-#' Data set with ~450 antibiotics
+#' Data sets with ~550 antimicrobials
#'
-#' A data set containing all antibiotics. Use \code{\link{as.ab}} or one of the \code{\link{ab_property}} functions to retrieve values from this data set. Three identifiers are included in this data set: an antibiotic ID (\code{ab}, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (\code{atc}) as defined by the WHO, and a Compound ID (\code{cid}) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
-#' @format A \code{\link{data.frame}} with 453 observations and 13 variables:
+#' Two data sets containing all antibiotics/antimycotics and antivirals. Use \code{\link{as.ab}} or one of the \code{\link{ab_property}} functions to retrieve values from the \code{antibiotics} data set. Three identifiers are included in this data set: an antibiotic ID (\code{ab}, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (\code{atc}) as defined by the WHO, and a Compound ID (\code{cid}) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
+#' @format
+#' \strong{For the \code{antibiotics} data set: a \code{\link{data.frame}} with 452 observations and 13 variables:}
#' \describe{
#' \item{\code{ab}}{Antibiotic ID as used in this package (like \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available}
#' \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like \code{J01CR02}}
@@ -38,7 +39,20 @@
#' \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
#' \item{\code{iv_units}}{Units of \code{iv_ddd}}
#' }
-#' @details Properties that are based on an ATC code are only available when an ATC is available. These properties are: \code{atc_group1}, \code{atc_group2}, \code{oral_ddd}, \code{oral_units}, \code{iv_ddd} and \code{iv_units}
+#'
+#' \strong{For the \code{antivirals} data set: a \code{\link{data.frame}} with 102 observations and 9 variables:}
+#' \describe{
+#' \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC}
+#' \item{\code{cid}}{Compound ID as found in PubChem}
+#' \item{\code{name}}{Official name as used by WHONET/EARS-Net or the WHO}
+#' \item{\code{atc_group}}{Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC}
+#' \item{\code{synonyms}}{Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID}
+#' \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
+#' \item{\code{oral_units}}{Units of \code{oral_ddd}}
+#' \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
+#' \item{\code{iv_units}}{Units of \code{iv_ddd}}
+#' }
+#' @details Properties that are based on an ATC code are only available when an ATC is available. These properties are: \code{atc_group1}, \code{atc_group2}, \code{oral_ddd}, \code{oral_units}, \code{iv_ddd} and \code{iv_units}.
#'
#' Synonyms (i.e. trade names) are derived from the Compound ID (\code{cid}) and consequently only available where a CID is available.
#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): \url{https://www.whocc.no/atc_ddd_index/}
@@ -48,26 +62,10 @@
#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}
#' @inheritSection WHOCC WHOCC
#' @inheritSection AMR Read more on our website!
-#' @seealso \code{\link{antivirals}} \code{\link{microorganisms}}
+#' @seealso \code{\link{microorganisms}}
"antibiotics"
-#' Data set with ~100 antivirals
-#'
-#' A data set containing all antivirals, according to the ATC code group 'J05' (Antivirals for systemic use).
-#' @format A \code{\link{data.frame}} with 102 observations and 7 variables:
-#' \describe{
-#' \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC}
-#' \item{\code{name}}{Official name as used by WHONET/EARS-Net or the WHO}
-#' \item{\code{atc_group}}{Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC}
-#' \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
-#' \item{\code{oral_units}}{Units of \code{oral_ddd}}
-#' \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
-#' \item{\code{iv_units}}{Units of \code{iv_ddd}}
-#' }
-#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): \url{https://www.whocc.no/atc_ddd_index/}
-#' @inheritSection WHOCC WHOCC
-#' @inheritSection AMR Read more on our website!
-#' @seealso \code{\link{antibiotics}} \code{\link{microorganisms}}
+#' @rdname antibiotics
"antivirals"
#' Data set with ~70,000 microorganisms
diff --git a/R/misc.R b/R/misc.R
index cfa1e8d6..37ae8870 100755
--- a/R/misc.R
+++ b/R/misc.R
@@ -29,6 +29,14 @@ addin_insert_like <- function() {
rstudioapi::insertText(" %like% ")
}
+load_AMR_package <- function() {
+ if (!"package:AMR" %in% base::search()) {
+ require(AMR)
+ # check onLoad() in R/zzz.R: data tables are created there.
+ }
+ base::invisible()
+}
+
#' @importFrom crayon blue bold red
#' @importFrom dplyr %>% pull
search_type_in_df <- function(x, type) {
diff --git a/R/mo.R b/R/mo.R
index 6e5eb645..b310c0c0 100755
--- a/R/mo.R
+++ b/R/mo.R
@@ -183,11 +183,14 @@
#' df <- df %>%
#' mutate(mo = as.mo(paste(genus, species)))
#' }
-as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain = TRUE, reference_df = get_mo_source(), ...) {
- if (!"AMR" %in% base::.packages()) {
- require("AMR")
- # check onLoad() in R/zzz.R: data tables are created there.
- }
+as.mo <- function(x,
+ Becker = FALSE,
+ Lancefield = FALSE,
+ allow_uncertain = TRUE,
+ reference_df = get_mo_source(),
+ ...) {
+
+ load_AMR_package()
# WHONET: xxx = no growth
x[tolower(as.character(paste0(x, ""))) %in% c("", "xxx", "na", "nan")] <- NA_character_
@@ -293,10 +296,7 @@ exec_as.mo <- function(x,
debug = FALSE,
reference_data_to_use = microorganismsDT) {
- if (!"AMR" %in% base::.packages()) {
- require("AMR")
- # check onLoad() in R/zzz.R: data tables are created there.
- }
+ load_AMR_package()
# WHONET: xxx = no growth
x[tolower(as.character(paste0(x, ""))) %in% c("", "xxx", "na", "nan")] <- NA_character_
diff --git a/R/mo_property.R b/R/mo_property.R
index eb9083b2..7f5cabf3 100755
--- a/R/mo_property.R
+++ b/R/mo_property.R
@@ -396,6 +396,8 @@ mo_property <- function(x, property = "fullname", language = get_locale(), ...)
}
mo_validate <- function(x, property, ...) {
+
+ load_AMR_package()
dots <- list(...)
Becker <- dots$Becker
@@ -407,11 +409,6 @@ mo_validate <- function(x, property, ...) {
Lancefield <- FALSE
}
- if (!"AMR" %in% base::.packages()) {
- require("AMR")
- # check .onLoad() in R/zzz.R: data tables are created there.
- }
-
# try to catch an error when inputting an invalid parameter
# so the 'call.' can be set to FALSE
tryCatch(x[1L] %in% AMR::microorganisms[1, property],
diff --git a/_pkgdown.yml b/_pkgdown.yml
index f74f913b..0e1359b0 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -155,14 +155,10 @@ reference:
'like' function can be useful: `if (x %like% y) {...}`.
contents:
- "`get_locale`"
- - "`like`"
- - title: Extended functions
- desc: >
- These functions are extensions of functions in other packages.
- contents:
- "`extended-functions`"
+ - "`like`"
- "`reexports`"
- - title: functions
+ - title: Deprecated functions
desc: >
These functions are deprecated, meaning that they will still
work but show a warning with every use and will be removed
diff --git a/data-raw/reproduction_of_antivirals.R b/data-raw/reproduction_of_antivirals.R
index 6f781161..230c24c1 100644
--- a/data-raw/reproduction_of_antivirals.R
+++ b/data-raw/reproduction_of_antivirals.R
@@ -57,6 +57,33 @@ for (i in 2:length(atc_groups)) {
antivirals <- rbind(antivirals, get_atc_table(atc_groups[i]))
}
-# arrange on name, untibble it and save
+# arrange on name, untibble it
antivirals <- antivirals %>% arrange(name) %>% as.data.frame(stringsAsFactors = FALSE)
+
+# add PubChem Compound ID (cid) and their trade names - functions are in file to create `antibiotics` data set
+CIDs <- get_CID(antivirals$name)
+# these could not be found:
+antivirals[is.na(CIDs),] %>% View()
+# get brand names from PubChem
+synonyms <- get_synonyms(CIDs)
+synonyms <- lapply(synonyms,
+ function(x) {
+ if (length(x) == 0 | all(is.na(x))) {
+ ""
+ } else {
+ x
+ }})
+
+antivirals <- antivirals %>%
+ transmute(atc,
+ cid = CIDs,
+ name,
+ atc_group,
+ synonyms = unname(synonyms),
+ oral_ddd,
+ oral_units,
+ iv_ddd,
+ iv_units)
+
+# save it
usethis::use_data(antivirals, overwrite = TRUE)
diff --git a/data/antivirals.rda b/data/antivirals.rda
index 8217fe01..8cda4848 100644
Binary files a/data/antivirals.rda and b/data/antivirals.rda differ
diff --git a/docs/404.html b/docs/404.html
index ae0ed72b..c62e2344 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -84,7 +84,7 @@
AMR (for R)
- 0.8.0.9033
+ 0.8.0.9034
diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html
index 1f557fd1..a8ddb657 100644
--- a/docs/LICENSE-text.html
+++ b/docs/LICENSE-text.html
@@ -84,7 +84,7 @@
AMR (for R)
- 0.8.0.9033
+ 0.8.0.9034
diff --git a/docs/articles/AMR.html b/docs/articles/AMR.html
index 9e658236..897c734e 100644
--- a/docs/articles/AMR.html
+++ b/docs/articles/AMR.html
@@ -41,7 +41,7 @@
AMR (for R)
- 0.8.0.9032
+ 0.8.0.9033
@@ -187,7 +187,7 @@
How to conduct AMR analysis
Matthijs S. Berends
-
18 November 2019
+
23 November 2019
AMR.Rmd
@@ -196,7 +196,7 @@
-
Note: values on this page will change with every website update since they are based on randomly created values and the page was written in R Markdown. However, the methodology remains unchanged. This page was generated on 18 November 2019.
+
Note: values on this page will change with every website update since they are based on randomly created values and the page was written in R Markdown. However, the methodology remains unchanged. This page was generated on 23 November 2019.
So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values M and F. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.
The data is already quite clean, but we still need to transform some variables. The bacteria column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The mutate() function of the dplyr package makes this really easy:
For future use, the above two syntaxes can be shortened with the filter_first_isolate() function:
@@ -510,7 +510,7 @@
First weighted isolates
-
We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient X7, sorted on date:
+
We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient T6, sorted on date:
Instead of 2, now 6 isolates are flagged. In total, 75.4% of all isolates are marked ‘first weighted’ - 46.9% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.
+
Instead of 2, now 10 isolates are flagged. In total, 75.5% of all isolates are marked ‘first weighted’ - 47.1% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.
As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (proportion_R(), equal to resistance()) and susceptibility as the proportion of S and I (proportion_SI(), equal to susceptibility()). These functions can be used on their own:
diff --git a/docs/articles/index.html b/docs/articles/index.html
index 130e31fb..6190f5b0 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -84,7 +84,7 @@
AMR (for R)
- 0.8.0.9033
+ 0.8.0.9034
diff --git a/docs/authors.html b/docs/authors.html
index 6f9ff702..deebbbe1 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -84,7 +84,7 @@
AMR (for R)
- 0.8.0.9033
+ 0.8.0.9034
diff --git a/docs/countries.png b/docs/countries.png
new file mode 100644
index 00000000..df8e944e
Binary files /dev/null and b/docs/countries.png differ
diff --git a/docs/extra.css b/docs/extra.css
index 2c97a9df..ae63a9a9 100644
--- a/docs/extra.css
+++ b/docs/extra.css
@@ -41,6 +41,11 @@
width: 19%;
min-width: 125px;
}
+.countries_map {
+ float: left;
+ padding: 0 10px 10px 0;
+ max-width: 25%;
+}
@media only screen and (max-width: 992px) {
.footer_logo {
float: left;
diff --git a/docs/index.html b/docs/index.html
index 2dd54fee..ff0de3c9 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -45,7 +45,7 @@
AMR (for R)
- 0.8.0.9033
+ 0.8.0.9034
@@ -200,10 +200,15 @@ A methods paper about this package has been preprinted at bioRxiv. It was update
What is AMR (for R)?
-
AMR is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Since its first public release in early 2018, this package has been downloaded over 25,000 times from more than 70 countries (source: CRAN logs, 2019).
AMR is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. After installing this package, R knows ~70,000 distinct microbial species and all ~550 antibiotic, antimycotic and antiviral drugs by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.
We created this package for both routine analysis and academic research (as part of our PhD theses) at the Faculty of Medical Sciences of the University of Groningen, the Netherlands, and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and is free software (see Copyright).
+
+ Used in over 70 countries
+ Since its first public release in early 2018, this package has been downloaded over 25,000 times from 74 countries (as of November 2019, CRAN logs). Click the map to enlarge.
diff --git a/docs/reference/antibiotics.html b/docs/reference/antibiotics.html
index 4724a72b..6b830065 100644
--- a/docs/reference/antibiotics.html
+++ b/docs/reference/antibiotics.html
@@ -6,7 +6,7 @@
-Data set with ~450 antibiotics — antibiotics • AMR (for R)
+Data sets with ~550 antimicrobials — antibiotics • AMR (for R)
@@ -50,8 +50,8 @@
-
-
+
+
@@ -85,7 +85,7 @@
AMR (for R)
- 0.8.0.9032
+ 0.8.0.9034
@@ -228,21 +228,23 @@
-
Data set with ~450 antibiotics
+
Data sets with ~550 antimicrobials
antibiotics.Rd
-
A data set containing all antibiotics. Use as.ab or one of the ab_property functions to retrieve values from this data set. Three identifiers are included in this data set: an antibiotic ID (ab, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (atc) as defined by the WHO, and a Compound ID (cid) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
+
Two data sets containing all antibiotics/antimycotics and antivirals. Use as.ab or one of the ab_property functions to retrieve values from the antibiotics data set. Three identifiers are included in this data set: an antibiotic ID (ab, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (atc) as defined by the WHO, and a Compound ID (cid) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
-
antibiotics
+
antibiotics
+
+antivirals
Format
-
A data.frame with 453 observations and 13 variables:
+
For the antibiotics data set: a data.frame with 452 observations and 13 variables:
ab
Antibiotic ID as used in this package (like AMC), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
atc
ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like J01CR02
cid
Compound ID as found in PubChem
@@ -257,6 +259,19 @@
iv_ddd
Defined Daily Dose (DDD), parenteral treatment
iv_units
Units of iv_ddd
+
+
+
For the antivirals data set: a data.frame with 102 observations and 9 variables:
+
atc
ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC
+
cid
Compound ID as found in PubChem
+
name
Official name as used by WHONET/EARS-Net or the WHO
+
atc_group
Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC
+
synonyms
Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID
Properties that are based on an ATC code are only available when an ATC is available. These properties are: atc_group1, atc_group2, oral_ddd, oral_units, iv_ddd and iv_units
+
Properties that are based on an ATC code are only available when an ATC is available. These properties are: atc_group1, atc_group2, oral_ddd, oral_units, iv_ddd and iv_units.
Synonyms (i.e. trade names) are derived from the Compound ID (cid) and consequently only available where a CID is available.
WHOCC
@@ -283,7 +298,7 @@ This package contains all ~550 antibiotic, antimycotic and antiviral dru
diff --git a/docs/reference/eucast_rules.html b/docs/reference/eucast_rules.html
index 09701e32..48fafcd2 100644
--- a/docs/reference/eucast_rules.html
+++ b/docs/reference/eucast_rules.html
@@ -86,7 +86,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
AMR (for R)
- 0.8.0.9032
+ 0.8.0.9033
diff --git a/docs/reference/mdro.html b/docs/reference/mdro.html
index 1a449711..f1d5c40d 100644
--- a/docs/reference/mdro.html
+++ b/docs/reference/mdro.html
@@ -85,7 +85,7 @@
AMR (for R)
- 0.8.0.9032
+ 0.8.0.9033
diff --git a/docs/reference/rsi_translation.html b/docs/reference/rsi_translation.html
index 2f74af5e..54166eb8 100644
--- a/docs/reference/rsi_translation.html
+++ b/docs/reference/rsi_translation.html
@@ -85,7 +85,7 @@
AMR (for R)
- 0.8.0.9032
+ 0.8.0.9033
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index 131eb24d..092414d3 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -27,9 +27,6 @@
https://msberends.gitlab.io/AMR/reference/antibiotics.html
-
- https://msberends.gitlab.io/AMR/reference/antivirals.html
- https://msberends.gitlab.io/AMR/reference/as.ab.html
diff --git a/index.md b/index.md
index c153a5ce..83ff5c74 100644
--- a/index.md
+++ b/index.md
@@ -10,13 +10,16 @@
### What is `AMR` (for R)?
-`AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Since its first public release in early 2018, this package has been downloaded over 25,000 times from more than 70 countries (source: [CRAN logs, 2019](https://cran-logs.rstudio.com)).
-
-After installing this package, R knows [**~70,000 distinct microbial species**](./reference/microorganisms.html) and all [**~550 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.
+`AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. After installing this package, R knows [**~70,000 distinct microbial species**](./reference/microorganisms.html) and all [**~550 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.
We created this package for both routine analysis and academic research (as part of our PhD theses) at the Faculty of Medical Sciences of the University of Groningen, the Netherlands, and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is [actively maintained](./news) and is free software (see [Copyright](#copyright)).
-**Used to SPSS?** Read our [tutorial on how to import data from SPSS, SAS or Stata](./articles/SPSS.html).
+
+
+
+ Used in over 70 countries
+ Since its first public release in early 2018, this package has been downloaded over 25,000 times from 74 countries (as of November 2019, CRAN logs). Click the map to enlarge.
+
#### Partners
diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd
index e694bf2c..4a826fe4 100644
--- a/man/antibiotics.Rd
+++ b/man/antibiotics.Rd
@@ -3,8 +3,9 @@
\docType{data}
\name{antibiotics}
\alias{antibiotics}
-\title{Data set with ~450 antibiotics}
-\format{A \code{\link{data.frame}} with 453 observations and 13 variables:
+\alias{antivirals}
+\title{Data sets with ~550 antimicrobials}
+\format{\strong{For the \code{antibiotics} data set: a \code{\link{data.frame}} with 452 observations and 13 variables:}
\describe{
\item{\code{ab}}{Antibiotic ID as used in this package (like \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available}
\item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like \code{J01CR02}}
@@ -19,6 +20,19 @@
\item{\code{oral_units}}{Units of \code{oral_ddd}}
\item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
\item{\code{iv_units}}{Units of \code{iv_ddd}}
+}
+
+\strong{For the \code{antivirals} data set: a \code{\link{data.frame}} with 102 observations and 9 variables:}
+\describe{
+ \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC}
+ \item{\code{cid}}{Compound ID as found in PubChem}
+ \item{\code{name}}{Official name as used by WHONET/EARS-Net or the WHO}
+ \item{\code{atc_group}}{Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC}
+ \item{\code{synonyms}}{Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID}
+ \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
+ \item{\code{oral_units}}{Units of \code{oral_ddd}}
+ \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
+ \item{\code{iv_units}}{Units of \code{iv_ddd}}
}}
\source{
World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): \url{https://www.whocc.no/atc_ddd_index/}
@@ -29,12 +43,14 @@ European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{htt
}
\usage{
antibiotics
+
+antivirals
}
\description{
-A data set containing all antibiotics. Use \code{\link{as.ab}} or one of the \code{\link{ab_property}} functions to retrieve values from this data set. Three identifiers are included in this data set: an antibiotic ID (\code{ab}, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (\code{atc}) as defined by the WHO, and a Compound ID (\code{cid}) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
+Two data sets containing all antibiotics/antimycotics and antivirals. Use \code{\link{as.ab}} or one of the \code{\link{ab_property}} functions to retrieve values from the \code{antibiotics} data set. Three identifiers are included in this data set: an antibiotic ID (\code{ab}, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (\code{atc}) as defined by the WHO, and a Compound ID (\code{cid}) as found in PubChem. Other properties in this data set are derived from one or more of these codes.
}
\details{
-Properties that are based on an ATC code are only available when an ATC is available. These properties are: \code{atc_group1}, \code{atc_group2}, \code{oral_ddd}, \code{oral_units}, \code{iv_ddd} and \code{iv_units}
+Properties that are based on an ATC code are only available when an ATC is available. These properties are: \code{atc_group1}, \code{atc_group2}, \code{oral_ddd}, \code{oral_units}, \code{iv_ddd} and \code{iv_units}.
Synonyms (i.e. trade names) are derived from the Compound ID (\code{cid}) and consequently only available where a CID is available.
}
@@ -56,6 +72,6 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
}
\seealso{
-\code{\link{antivirals}} \code{\link{microorganisms}}
+\code{\link{microorganisms}}
}
\keyword{datasets}
diff --git a/man/antivirals.Rd b/man/antivirals.Rd
deleted file mode 100644
index a3306fd8..00000000
--- a/man/antivirals.Rd
+++ /dev/null
@@ -1,46 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/data.R
-\docType{data}
-\name{antivirals}
-\alias{antivirals}
-\title{Data set with ~100 antivirals}
-\format{A \code{\link{data.frame}} with 102 observations and 7 variables:
-\describe{
- \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC}
- \item{\code{name}}{Official name as used by WHONET/EARS-Net or the WHO}
- \item{\code{atc_group}}{Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC}
- \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
- \item{\code{oral_units}}{Units of \code{oral_ddd}}
- \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
- \item{\code{iv_units}}{Units of \code{iv_ddd}}
-}}
-\source{
-World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): \url{https://www.whocc.no/atc_ddd_index/}
-}
-\usage{
-antivirals
-}
-\description{
-A data set containing all antivirals, according to the ATC code group 'J05' (Antivirals for systemic use).
-}
-\section{WHOCC}{
-
-\if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr}
-This package contains \strong{all ~550 antibiotic, antimycotic and antiviral drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}).
-
-These have become the gold standard for international drug utilisation monitoring and research.
-
-The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.
-
-\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.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
-}
-
-\seealso{
-\code{\link{antibiotics}} \code{\link{microorganisms}}
-}
-\keyword{datasets}
diff --git a/pkgdown/extra.css b/pkgdown/extra.css
index 2c97a9df..ae63a9a9 100644
--- a/pkgdown/extra.css
+++ b/pkgdown/extra.css
@@ -41,6 +41,11 @@
width: 19%;
min-width: 125px;
}
+.countries_map {
+ float: left;
+ padding: 0 10px 10px 0;
+ max-width: 25%;
+}
@media only screen and (max-width: 992px) {
.footer_logo {
float: left;
diff --git a/pkgdown/logos/countries.png b/pkgdown/logos/countries.png
new file mode 100644
index 00000000..df8e944e
Binary files /dev/null and b/pkgdown/logos/countries.png differ
+ Used in over 70 countries