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mean AMR distance

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dr. M.S. (Matthijs) Berends 2022-10-21 15:59:31 +02:00
parent 4bebba3610
commit 178ab5e5ff
5 changed files with 13 additions and 13 deletions
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2
DESCRIPTION
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@ -1,5 +1,5 @@
Package: AMR
Version: 1.8.2.9027
Version: 1.8.2.9028
Date: 2022-10-21
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

2
NAMESPACE
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@ -225,7 +225,6 @@ export(count_resistant)
export(count_susceptible)
export(custom_eucast_rules)
export(custom_mdro_guideline)
export(distance_from_row)
export(eucast_dosage)
export(eucast_exceptional_phenotypes)
export(eucast_rules)
@ -266,6 +265,7 @@ export(mdr_cmi2012)
export(mdr_tb)
export(mdro)
export(mean_amr_distance)
export(mean_distance_from_row)
export(mo_authors)
export(mo_class)
export(mo_cleaning_regex)

4
NEWS.md
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@ -1,4 +1,4 @@
# AMR 1.8.2.9027
# AMR 1.8.2.9028
This version will eventually become v2.0! We're happy to reach a new major milestone soon!
@ -27,7 +27,7 @@ This version will eventually become v2.0! We're happy to reach a new major miles
* Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 16 languages. The automatic language determination will give a note at start-up on systems in supported languages.
* Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info [in this article on our website](https://msberends.github.io/AMR/articles/datasets.html).
* Added confidence intervals in AMR calculation. This is now included in `rsi_df()` and `proportion_df()` and manually available as `rsi_confidence_interval()`
* Support for using antibiotic selectors in scoped `dplyr` verbs (worh or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`
* Support for using antibiotic selectors in scoped `dplyr` verbs (with or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`, see `resistance()`
### Changed
* Fix for using `as.rsi()` on certain EUCAST breakpoints for MIC values

8
R/mean_amr_distance.R
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@ -41,7 +41,7 @@
#'
#' For data sets, the mean AMR distance will be calculated per variable, after which the mean of all columns will returned per row (using [rowMeans()]), see *Examples*.
#'
#' Use [distance_from_row()] to subtract distances from the distance of one row, see *Examples*.
#' Use [mean_distance_from_row()] to subtract distances from the distance of one row, see *Examples*.
#' @section Interpretation:
#' Isolates with distances less than 0.01 difference from each other should be considered similar. Differences lower than 0.025 should be considered suspicious.
#' @export
@ -66,7 +66,7 @@
#' y %>%
#' mutate(
#' amr_distance = mean_amr_distance(., where(is.mic)),
#' check_id_C = distance_from_row(amr_distance, id == "C")
#' check_id_C = mean_distance_from_row(amr_distance, id == "C")
#' ) %>%
#' arrange(check_id_C)
#' }
@ -104,7 +104,7 @@ mean_amr_distance.disk <- function(x, ...) {
#' @rdname mean_amr_distance
#' @export
mean_amr_distance.rsi <- function(x, combine_SI = TRUE, ...) {
mean_amr_distance.rsi <- function(x, ..., combine_SI = TRUE) {
meet_criteria(combine_SI, allow_class = "logical", has_length = 1, .call_depth = -1)
if (isTRUE(combine_SI)) {
x[x == "I"] <- "S"
@ -157,7 +157,7 @@ mean_amr_distance.data.frame <- function(x, ..., combine_SI = TRUE) {
#' @param mean_distance the outcome of [mean_amr_distance()]
#' @param row an index, such as a row number
#' @export
distance_from_row <- function(mean_distance, row) {
mean_distance_from_row <- function(mean_distance, row) {
meet_criteria(mean_distance, allow_class = c("double", "numeric"), is_finite = TRUE)
meet_criteria(row, allow_class = c("logical", "double", "numeric"))
if (is.logical(row)) {

10
man/mean_amr_distance.Rd
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@ -7,7 +7,7 @@
\alias{mean_amr_distance.disk}
\alias{mean_amr_distance.rsi}
\alias{mean_amr_distance.data.frame}
\alias{distance_from_row}
\alias{mean_distance_from_row}
\title{Mean AMR Distance}
\usage{
mean_amr_distance(x, ...)
@ -18,11 +18,11 @@ mean_amr_distance(x, ...)
\method{mean_amr_distance}{disk}(x, ...)
\method{mean_amr_distance}{rsi}(x, combine_SI = TRUE, ...)
\method{mean_amr_distance}{rsi}(x, ..., combine_SI = TRUE)
\method{mean_amr_distance}{data.frame}(x, ..., combine_SI = TRUE)
distance_from_row(mean_distance, row)
mean_distance_from_row(mean_distance, row)
}
\arguments{
\item{x}{a vector of class \link[=as.rsi]{rsi}, \link[=as.rsi]{rsi} or \link[=as.rsi]{rsi}, or a \link{data.frame} containing columns of any of these classes}
@ -47,7 +47,7 @@ R/SI values (see \code{\link[=as.rsi]{as.rsi()}}) are transformed using \code{"S
For data sets, the mean AMR distance will be calculated per variable, after which the mean of all columns will returned per row (using \code{\link[=rowMeans]{rowMeans()}}), see \emph{Examples}.
Use \code{\link[=distance_from_row]{distance_from_row()}} to subtract distances from the distance of one row, see \emph{Examples}.
Use \code{\link[=mean_distance_from_row]{mean_distance_from_row()}} to subtract distances from the distance of one row, see \emph{Examples}.
}
\section{Interpretation}{
@ -75,7 +75,7 @@ if (require("dplyr")) {
y \%>\%
mutate(
amr_distance = mean_amr_distance(., where(is.mic)),
check_id_C = distance_from_row(amr_distance, id == "C")
check_id_C = mean_distance_from_row(amr_distance, id == "C")
) \%>\%
arrange(check_id_C)
}