First CRAN submission edits

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: AMR
-Version: 0.1.0
+Version: 0.1.1
-Date: 2018-02-20
+Date: 2018-02-22
-Title: Antimicrobial Resistance (AMR) Analysis
+Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(
         given = c("Matthijs", "S."),
@@ -20,7 +20,8 @@ Authors@R: c(
         role = "ctb"))
 Description: Functions to simplify the analysis of Antimicrobial Resistance (AMR)
     of microbial isolates, by using new S3 classes and applying EUCAST expert rules
-    on antibiograms.
+    on antibiograms according to Leclercq (2013)
+    <doi:10.1111/j.1469-0691.2011.03703.x>.
 Depends: R (>= 3.0)
 Imports: dplyr (>= 0.7.0), reshape2 (>= 1.4.0), xml2, rvest
 URL: https://github.com/msberends/AMR

NAMESPACE

@@ -21,7 +21,6 @@ export(interpretive_reading)
 export(is.mic)
 export(is.rsi)
 export(key_antibiotics)
-export(key_antibiotics_equal)
 export(left_join_bactlist)
 export(mo_property)
 export(right_join_bactlist)

R/EUCAST.R

@@ -28,6 +28,7 @@
 #' @rdname EUCAST
 #' @export
 #' @importFrom dplyr %>% left_join select
+#' @return table with edited variables of antibiotics.
 #' @source
 #'   EUCAST Expert Rules Version 2.0: \cr
 #'   Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility testing.} \emph{Clin Microbiol Infect.} 2013;19(2):141-60. \cr
@@ -37,7 +38,7 @@
 #'   \url{http://www.eucast.org/expert_rules_and_intrinsic_resistance}
 #' @examples
 #' \dontrun{
-#' tbl <- interpretive_reading(tbl)
+#' tbl <- EUCAST_rules(tbl)
 #' }
 EUCAST_rules <- function(tbl,
                          col_bactcode = 'bacteriecode',

R/atc.R

@@ -18,7 +18,7 @@
 
 #' Properties of an ATC code
 #'
-#' Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic.
+#' Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic. \strong{This function requires an internet connection.}
 #' @param atc_code a character or character vector with ATC code(s) of antibiotic(s)
 #' @param property property of an ATC code. Valid values are \code{"ATC code"}, \code{"Name"}, \code{"DDD"}, \code{"U"} (\code{"unit"}), \code{"Adm.R"} en \code{"Note"}.
 #' @param administration type of administration, see \emph{Details}
@@ -54,6 +54,11 @@
 #' @importFrom xml2 read_html
 #' @importFrom rvest html_nodes html_table
 #' @source \url{https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/}
+#' @examples 
+#' \donttest{
+#' atc_property("J01CA04", "DDD", "O") # oral DDD of amoxicillin
+#' atc_property("J01CA04", "DDD", "P") # parenteral DDD of amoxicillin
+#' }
 atc_property <- function(atc_code,
                          property,
                          administration = 'O',
@@ -128,6 +133,7 @@ atc_property <- function(atc_code,
 #' @param textbetween text to put between multiple returned texts
 #' @param tolower return output as lower case with function \code{\link{tolower}}.
 #' @keywords ab antibiotics
+#' @source \code{\link{ablist}}
 #' @export
 #' @importFrom dplyr %>% filter select slice 
 #' @examples
@@ -148,8 +154,6 @@ atc_property <- function(atc_code,
 #'
 #' abname("J01CR02", from = "atc", to = "umcg")
 #' # "AMCL"
-#'
-#' @source \code{\link{ablist}}
 abname <- function(abcode, from = 'umcg', to = 'official', textbetween = ' + ', tolower = FALSE) {
   
   ablist <- AMR::ablist

R/classes.R

@@ -26,8 +26,16 @@
 #' @importFrom dplyr %>%
 #' @examples
 #' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
-#' 
 #' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
+#' is.rsi(rsi_data)
+#' plot(rsi_data)
+#' 
+#' \donttest{
+#' library(dplyr)
+#' tbl %>%
+#'   mutate_at(vars(ends_with("_rsi")), as.rsi)
+#' sapply(mic_data, is.rsi)
+#' }
 as.rsi <- function(x) {
   if (is.rsi(x)) {
     x
@@ -157,6 +165,17 @@ plot.rsi <- function(x, ...) {
 #' @return New class \code{mic}
 #' @export
 #' @importFrom dplyr %>%
+#' @examples
+#' mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
+#' is.mic(mic_data)
+#' plot(mic_data)
+#' 
+#' \donttest{
+#' library(dplyr)
+#' tbl %>%
+#'   mutate_at(vars(ends_with("_mic")), as.mic)
+#' sapply(mic_data, is.mic)
+#' }
 as.mic <- function(x, na.rm = FALSE) {
   if (is.mic(x)) {
     x

R/first_isolates.R

@@ -46,6 +46,7 @@
 #' @examples
 #' \dontrun{
 #'
+#' # set key antibiotics to a new variable
 #' tbl$keyab <- key_antibiotics(tbl)
 #'
 #' tbl$first_isolate <-
@@ -355,7 +356,13 @@ first_isolate <- function(tbl,
 #' @param amcl,amox,cfot,cfta,cftr,cfur,cipr,clar,clin,clox,doxy,gent,line,mero,peni,pita,rifa,teic,trsu,vanc column names of antibiotics.
 #' @export
 #' @importFrom dplyr %>% mutate if_else 
+#' @return Character of length 1.
 #' @seealso \code{\link{mo_property}} \code{\link{ablist}}
+#' @examples 
+#' \donttest{
+#' #' # set key antibiotics to a new variable
+#' tbl$keyab <- key_antibiotics(tbl)
+#' }
 key_antibiotics <- function(tbl,
                             col_bactcode = 'bacteriecode',
                             info = TRUE,
@@ -439,15 +446,17 @@ key_antibiotics <- function(tbl,
   
 }
 
-#' Compare key antibiotics
+# Compare key antibiotics
-#'
+#
-#' Check whether two text values with key antibiotics match. Supports vectors.
+# Check whether two text values with key antibiotics match. Supports vectors.
-#' @param x,y tekst (or multiple text vectors) with antimicrobial interpretations
+# @param x,y tekst (or multiple text vectors) with antimicrobial interpretations
-#' @param ignore_I ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)
+# @param ignore_I ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)
-#' @param info print progress
+# @param info print progress
-#' @return logical
+# @return logical
-#' @export
+# @export
-#' @seealso \code{\link{key_antibiotics}}
+# @seealso \code{\link{key_antibiotics}}
+
+# only internal use
 key_antibiotics_equal <- function(x, y, ignore_I = TRUE, info = FALSE) {
   if (length(x) != length(y)) {
     stop('Length of `x` and `y` must be equal.')

R/join.R

@@ -1,4 +1,4 @@
-#' Join van tabel en \code{bactlist}
+#' Join a table with \code{bactlist}
 #'
 #' Join the list of microorganisms \code{\link{bactlist}} easily to an existing table.
 #' @rdname join
@@ -9,6 +9,17 @@
 #' @param ... other parameters to pass trhough to \code{dplyr::\link[dplyr]{join}}.
 #' @details As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
 #' @export
+#' @examples 
+#' df <- data.frame(date = seq(from = as.Date("2018-01-01"),
+#'                             to = as.Date("2018-01-07"),
+#'                             by = 1),
+#'                  bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
+#'                                  "ESCCOL", "ESCCOL", "ESCCOL"),
+#'                  stringsAsFactors = FALSE)
+#'                  
+#' colnames(df)
+#' df2 <- left_join_bactlist(df, "bacteria_id")
+#' colnames(df2)
 inner_join_bactlist <- function(x, by = 'bactid', ...) {
   # no name set to `by` parameter
   if (is.null(names(by))) {

R/rsi_analysis.R

@@ -167,7 +167,7 @@ rsi_df <- function(tbl,
 
 #' Resistance of isolates
 #'
-#' This function can be used in \code{\link[dplyr]{summarise}}, see \emph{Examples}. CaBerekent het percentage S, SI, I, IR of R van een lijst isolaten. 
+#' This function can be used in \code{dplyr}s \code{\link[dplyr]{summarise}}, see \emph{Examples}. Calculate the percentage S, SI, I, IR or R of a vector of isolates.
 #' @param ab1,ab2 list with interpretations of an antibiotic
 #' @inheritParams rsi_df
 #' @details This function uses the \code{\link{rsi_df}} function internally.
@@ -177,20 +177,19 @@ rsi_df <- function(tbl,
 #' @examples
 #' \dontrun{
 #' tbl %>%
-#'   group_by(year, hospital) %>%
-#'   summarise(
-#'     isolates = n(),
-#'     cipro = rsi(cipr, percent = TRUE),
-#'     amoxi = rsi(amox, percent = TRUE)
-#'   )
-#'
-#' tbl %>%
 #'   group_by(hospital) %>%
 #'   summarise(cipr = rsi(cipr))
 #'   
-#' rsi(isolates$amox)
+#' tbl %>%
+#'   group_by(year, hospital) %>%
+#'   summarise(
+#'     isolates = n(),
+#'     cipro = rsi(cipr %>% as.rsi(), percent = TRUE),
+#'     amoxi = rsi(amox %>% as.rsi(), percent = TRUE))
 #'     
-#' rsi(isolates$amcl, interpretation = "S")
+#' rsi(as.rsi(isolates$amox))
+#'
+#' rsi(as.rsi(isolates$amcl), interpretation = "S")
 #' }
 rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FALSE, info = FALSE, warning = FALSE) {
   functietekst <- as.character(match.call())
@@ -258,6 +257,7 @@ rsi <- function(ab1, ab2 = NA, interpretation = 'IR', minimum = 30, percent = FA
 #' rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], "amcl")
 #'   
 #' # or with dplyr so you can actually read it:
+#' library(dplyr)
 #' tbl %>%
 #'   filter(first_isolate == TRUE,
 #'          genus == "Haemophilus") %>%

README.md

@@ -12,6 +12,26 @@ AMR can also be predicted for the forthcoming years with the `rsi_predict` funct
 
 It also contains functions to translate antibiotic codes from the lab (like `"AMOX"`) or the [WHO](https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no) (like `"J01CA04"`) to trivial names (like `"amoxicillin"`) and vice versa.
 
+## How to get it?
+[![CRAN_Badge](http://www.r-pkg.org/badges/version/AMR)](http://cran.r-project.org/package=AMR)
+
+This package is available on CRAN (latest stable version) and also here on GitHub (latest development version).
+
+#### Latest stable version from CRAN (recommended)
+RStudio:
+-  Click on `Tools` and then `Install Packages..`
+-  Type in `AMR` and press <kbd>Install</kbd>
+
+Other:
+```r
+install.packages("AMR")
+```
+
+#### Latest development version from GitHub
+```r
+devtools::install_github("msberends/AMR")
+```
+
 ## How to use it?
 ```r
 # Call it with:
@@ -95,28 +115,6 @@ abname(...)
 abname("J01CR02", from = "atc", to = "umcg") # "AMCL"
 ```
 
-## How to get it?
-This package is only available here on GitHub, but respects the [CRAN Repository Policy](https://cran.r-project.org/web/packages/policies.html).
-
-*Installation commands:*
-```r
-library(devtools)
-install_github("msberends/AMR")
-```
-
-*Working behind a proxy? Then use:*
-```r
-library(httr)
-library(devtools)
-set_config(use_proxy("yourproxydomain.com",
-                     8080,
-                     "username",
-                     "password",
-                     "any")) # change "any" to "basic" or "digest" if needed
-install_github("msberends/AMR")
-reset_config()
-```
-
 ## Authors
 
   - [Berends MS](https://github.com/msberends)<sup>1,2</sup>, PhD Student

man/EUCAST.Rd

@@ -44,11 +44,14 @@ interpretive_reading(...)
 
 \item{...}{parameters that are passed on to \code{EUCAST_rules}}
 }
+\value{
+table with edited variables of antibiotics.
+}
 \description{
 Apply expert rules (like intrinsic resistance), as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{http://eucast.org}), see \emph{Source}.
 }
 \examples{
 \dontrun{
-tbl <- interpretive_reading(tbl)
+tbl <- EUCAST_rules(tbl)
 }
 }

man/abname.Rd

@@ -40,7 +40,6 @@ abname("AMCL", to = "atc")
 
 abname("J01CR02", from = "atc", to = "umcg")
 # "AMCL"
-
 }
 \keyword{ab}
 \keyword{antibiotics}

man/as.mic.Rd

@@ -20,3 +20,15 @@ New class \code{mic}
 \description{
 This transforms a vector to a new class\code{mic}, which is an ordered factor valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
 }
+\examples{
+mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
+is.mic(mic_data)
+plot(mic_data)
+
+\donttest{
+library(dplyr)
+tbl \%>\%
+  mutate_at(vars(ends_with("_mic")), as.mic)
+sapply(mic_data, is.mic)
+}
+}

man/as.rsi.Rd

@@ -20,6 +20,14 @@ This transforms a vector to a new class \code{rsi}, which is an ordered factor w
 }
 \examples{
 rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
-
 rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
+is.rsi(rsi_data)
+plot(rsi_data)
+
+\donttest{
+library(dplyr)
+tbl \%>\%
+  mutate_at(vars(ends_with("_rsi")), as.rsi)
+sapply(mic_data, is.rsi)
+}
 }

man/atc_property.Rd

@@ -20,7 +20,7 @@ atc_property(atc_code, property, administration = "O",
 \item{url}{url of website of the WHO. The sign \code{\%s} can be used as a placeholder for ATC codes.}
 }
 \description{
-Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic.
+Gets data from the WHO to determine properties of an ATC of e.g. an antibiotic. \strong{This function requires an internet connection.}
 }
 \details{
 Abbreviations for the property \code{"Adm.R"} (parameter \code{administration}):
@@ -49,3 +49,9 @@ Abbreviations for the property \code{"U"} (unit):
   \item{\code{"ml"}}{ = milliliter (e.g. eyedrops)}
 }
 }
+\examples{
+\donttest{
+atc_property("J01CA04", "DDD", "O") # oral DDD of amoxicillin
+atc_property("J01CA04", "DDD", "P") # parenteral DDD of amoxicillin
+}
+}

man/first_isolate.Rd

@@ -57,6 +57,7 @@ To conduct an analysis of antimicrobial resistance, you should only include the
 \examples{
 \dontrun{
 
+# set key antibiotics to a new variable
 tbl$keyab <- key_antibiotics(tbl)
 
 tbl$first_isolate <-

man/join.Rd

@@ -9,7 +9,7 @@
 \alias{full_join_bactlist}
 \alias{semi_join_bactlist}
 \alias{anti_join_bactlist}
-\title{Join van tabel en \code{bactlist}}
+\title{Join a table with \code{bactlist}}
 \usage{
 inner_join_bactlist(x, by = "bactid", ...)
 
@@ -36,3 +36,15 @@ Join the list of microorganisms \code{\link{bactlist}} easily to an existing tab
 \details{
 As opposed to the \code{\link[dplyr]{join}} functions of \code{dplyr}, at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr]{join}} for more information.
 }
+\examples{
+df <- data.frame(date = seq(from = as.Date("2018-01-01"),
+                            to = as.Date("2018-01-07"),
+                            by = 1),
+                 bacteria_id = c("STAAUR", "STAAUR", "STAAUR", "STAAUR",
+                                 "ESCCOL", "ESCCOL", "ESCCOL"),
+                 stringsAsFactors = FALSE)
+                 
+colnames(df)
+df2 <- left_join_bactlist(df, "bacteria_id")
+colnames(df2)
+}

man/key_antibiotics.Rd

@@ -20,9 +20,18 @@ key_antibiotics(tbl, col_bactcode = "bacteriecode", info = TRUE,
 
 \item{amcl, amox, cfot, cfta, cftr, cfur, cipr, clar, clin, clox, doxy, gent, line, mero, peni, pita, rifa, teic, trsu, vanc}{column names of antibiotics.}
 }
+\value{
+Character of length 1.
+}
 \description{
 Key antibiotics based on bacteria ID
 }
+\examples{
+\donttest{
+#' # set key antibiotics to a new variable
+tbl$keyab <- key_antibiotics(tbl)
+}
+}
 \seealso{
 \code{\link{mo_property}} \code{\link{ablist}}
 }

man/key_antibiotics_equal.Rd

@@ -1,24 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/first_isolates.R
-\name{key_antibiotics_equal}
-\alias{key_antibiotics_equal}
-\title{Compare key antibiotics}
-\usage{
-key_antibiotics_equal(x, y, ignore_I = TRUE, info = FALSE)
-}
-\arguments{
-\item{x, y}{tekst (or multiple text vectors) with antimicrobial interpretations}
-
-\item{ignore_I}{ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)}
-
-\item{info}{print progress}
-}
-\value{
-logical
-}
-\description{
-Check whether two text values with key antibiotics match. Supports vectors.
-}
-\seealso{
-\code{\link{key_antibiotics}}
-}

man/rsi.Rd

@@ -24,28 +24,27 @@ rsi(ab1, ab2 = NA, interpretation = "IR", minimum = 30, percent = FALSE,
 Double or, when \code{percent = TRUE}, a character.
 }
 \description{
-This function can be used in \code{\link[dplyr]{summarise}}, see \emph{Examples}. CaBerekent het percentage S, SI, I, IR of R van een lijst isolaten.
+This function can be used in \code{dplyr}s \code{\link[dplyr]{summarise}}, see \emph{Examples}. Calculate the percentage S, SI, I, IR or R of a vector of isolates.
 }
 \details{
 This function uses the \code{\link{rsi_df}} function internally.
 }
 \examples{
 \dontrun{
-tbl \%>\%
-  group_by(year, hospital) \%>\%
-  summarise(
-    isolates = n(),
-    cipro = rsi(cipr, percent = TRUE),
-    amoxi = rsi(amox, percent = TRUE)
-  )
-
 tbl \%>\%
   group_by(hospital) \%>\%
   summarise(cipr = rsi(cipr))
   
-rsi(isolates$amox)
+tbl \%>\%
+  group_by(year, hospital) \%>\%
+  summarise(
+    isolates = n(),
+    cipro = rsi(cipr \%>\% as.rsi(), percent = TRUE),
+    amoxi = rsi(amox \%>\% as.rsi(), percent = TRUE))
     
-rsi(isolates$amcl, interpretation = "S")
+rsi(as.rsi(isolates$amox))
+
+rsi(as.rsi(isolates$amcl), interpretation = "S")
 }
 }
 \keyword{antibiotics}

man/rsi_predict.Rd

@@ -40,6 +40,7 @@ Create a prediction model to predict antimicrobial resistance for the next years
 rsi_predict(tbl[which(first_isolate == TRUE & genus == "Haemophilus"),], "amcl")
   
 # or with dplyr so you can actually read it:
+library(dplyr)
 tbl \%>\%
   filter(first_isolate == TRUE,
          genus == "Haemophilus") \%>\%