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emph guess_bactid

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  1. 1
      .travis.yml
  2. 2
      NEWS.md
  3. 26
      R/bactid.R
  4. 4
      README.md
  5. 9
      man/as.bactid.Rd

1
.travis.yml

@ -33,7 +33,6 @@ jobs: @@ -33,7 +33,6 @@ jobs:
matrix:
allow_failures:
- r: 3.1
- r: 3.2
- r: devel
r_packages: covr
cache: packages

2
NEWS.md

@ -7,7 +7,7 @@ @@ -7,7 +7,7 @@
* Universal: amoxicillin, amoxicillin/clavlanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole
* Gram-positive: vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampicin
* Gram-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem
* Functions `as.bactid` and `is.bactid` to transform/look up microbial ID's; this replaces the function `guess_bactid` but it will remain available for backwards compatibility
* Functions `as.bactid` and `is.bactid` to transform/look up microbial ID's
* For convience, new descriptive statistical functions `kurtosis` and `skewness` that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices
* Function `g.test` to perform the Χ<sup>2</sup> distributed [*G*-test](https://en.wikipedia.org/wiki/G-test), which use is the same as `chisq.test`
* Function `ratio` to transform a vector of values to a preset ratio

26
R/bactid.R

@ -21,7 +21,9 @@ @@ -21,7 +21,9 @@
#' Use this function to determine a valid ID based on a genus (and species). This input can be a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), or just a genus. You could also \code{\link{select}} a genus and species column, zie Examples.
#' @param x a character vector or a dataframe with one or two columns
#' @rdname as.bactid
#' @details Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. For example:
#' @details \code{guess_bactid} does exactly the same as \code{as.bactid}.
#'
#' Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. For example:
#' \itemize{
#' \item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
#' \item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae}}
@ -53,17 +55,16 @@ @@ -53,17 +55,16 @@
#' library(dplyr)
#' df$bactid <- df %>%
#' select(microorganism_name) %>%
#' as.bactid()
#' guess_bactid()
#'
#' # and can even contain 2 columns, which is convenient for genus/species combinations:
#' df$bactid <- df %>%
#' select(genus, species) %>%
#' as.bactid()
#' guess_bactid()
#'
#' # same result:
#' df <- df %>%
#' mutate(bactid = paste(genus, species) %>%
#' as.bactid())
#' mutate(bactid = guess_bactid(paste(genus, species)))
#' }
as.bactid <- function(x) {
@ -158,7 +159,8 @@ as.bactid <- function(x) { @@ -158,7 +159,8 @@ as.bactid <- function(x) {
next
}
if (toupper(x.backup[i]) == 'MRSE') {
x[i] <- 'Staphylococcus epidermidis'
x[i] <- 'STAEPI'
next
}
if (toupper(x.backup[i]) == 'VRE') {
x[i] <- 'ENC'
@ -169,15 +171,9 @@ as.bactid <- function(x) { @@ -169,15 +171,9 @@ as.bactid <- function(x) {
x[i] <- 'PSEAER'
next
}
if (toupper(x.backup[i]) == 'PISP'
| toupper(x.backup[i]) == 'PRSP') {
# peni resistant S. pneumoniae
x[i] <- 'Streptococcus pneumoniae'
}
if (toupper(x.backup[i]) == 'VISP'
| toupper(x.backup[i]) == 'VRSP') {
# vanco resistant S. pneumoniae
x[i] <- 'Streptococcus pneumoniae'
if (toupper(x.backup[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) {
# peni R, peni I, vanco I, vanco R: S. pneumoniae
x[i] <- 'STCPNE'
}
}

4
README.md

@ -53,9 +53,9 @@ The functions to calculate microbial resistance use expressions that are not eva @@ -53,9 +53,9 @@ The functions to calculate microbial resistance use expressions that are not eva
This package [is published on CRAN](http://cran.r-project.org/package=AMR), the official R network.
### Install from CRAN (recommended)
[![CRAN_Badge](https://img.shields.io/cran/v/AMR.svg?label=CRAN)](http://cran.r-project.org/package=AMR) [![CRAN_Downloads](https://cranlogs.r-pkg.org/badges/grand-total/AMR)](http://cran.r-project.org/package=AMR)
[![CRAN_Badge](https://img.shields.io/cran/v/AMR.svg?label=CRAN&colorB=3679BC)](http://cran.r-project.org/package=AMR) [![CRAN_Downloads](https://cranlogs.r-pkg.org/badges/grand-total/AMR)](http://cran.r-project.org/package=AMR)
(Note: downloads measured only by [cran.rstudio.com](https://cran.rstudio.com/package=AMR), i.e. this excludes the official [cran.r-project.org](https://cran.r-project.org/package=AMR))
(Note: Downloads measured only by [cran.rstudio.com](https://cran.rstudio.com/package=AMR), this excludes e.g. the official [cran.r-project.org](https://cran.r-project.org/package=AMR))
- <img src="http://www.rstudio.com/favicon.ico" alt="RStudio favicon" height="20px"> Install using [RStudio](http://www.rstudio.com) (recommended):
- Click on `Tools` and then `Install Packages...`

9
man/as.bactid.Rd

@ -22,6 +22,8 @@ Character (vector) with class \code{"bactid"}. Unknown values will return \code{ @@ -22,6 +22,8 @@ Character (vector) with class \code{"bactid"}. Unknown values will return \code{
Use this function to determine a valid ID based on a genus (and species). This input can be a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), or just a genus. You could also \code{\link{select}} a genus and species column, zie Examples.
}
\details{
\code{guess_bactid} does exactly the same as \code{as.bactid}.
Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. For example:
\itemize{
\item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
@ -51,17 +53,16 @@ df$bactid <- as.bactid(df$microorganism_name) @@ -51,17 +53,16 @@ df$bactid <- as.bactid(df$microorganism_name)
library(dplyr)
df$bactid <- df \%>\%
select(microorganism_name) \%>\%
as.bactid()
guess_bactid()
# and can even contain 2 columns, which is convenient for genus/species combinations:
df$bactid <- df \%>\%
select(genus, species) \%>\%
as.bactid()
guess_bactid()
# same result:
df <- df \%>\%
mutate(bactid = paste(genus, species) \%>\%
as.bactid())
mutate(bactid = guess_bactid(paste(genus, species)))
}
}
\seealso{

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