% Generated by roxygen2: do not edit by hand % Please edit documentation in R/mic.R \docType{data} \name{as.mic} \alias{as.mic} \alias{mic} \alias{is.mic} \alias{NA_mic_} \alias{rescale_mic} \alias{droplevels.mic} \title{Transform Input to Minimum Inhibitory Concentrations (MIC)} \usage{ as.mic(x, na.rm = FALSE, keep_operators = "all") is.mic(x) NA_mic_ rescale_mic(x, mic_range, keep_operators = "edges", as.mic = TRUE) \method{droplevels}{mic}(x, as.mic = FALSE, ...) } \arguments{ \item{x}{a \link{character} or \link{numeric} vector} \item{na.rm}{a \link{logical} indicating whether missing values should be removed} \item{keep_operators}{a \link{character} specifying how to handle operators (such as \code{>} and \code{<=}) in the input. Accepts one of three values: \code{"all"} (or \code{TRUE}) to keep all operators, \code{"none"} (or \code{FALSE}) to remove all operators, or \code{"edges"} to keep operators only at both ends of the range.} \item{mic_range}{a manual range to limit the MIC values, e.g., \code{mic_range = c(0.001, 32)}. Use \code{NA} to set no limit on one side, e.g., \code{mic_range = c(NA, 32)}.} \item{as.mic}{a \link{logical} to indicate whether the \code{mic} class should be kept - the default is \code{FALSE}} \item{...}{arguments passed on to methods} } \value{ Ordered \link{factor} with additional class \code{\link{mic}}, that in mathematical operations acts as a \link{numeric} vector. Bear in mind that the outcome of any mathematical operation on MICs will return a \link{numeric} value. } \description{ This transforms vectors to a new class \code{\link{mic}}, which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology. } \details{ To interpret MIC values as SIR values, use \code{\link[=as.sir]{as.sir()}} on MIC values. It supports guidelines from EUCAST (2011-2023) and CLSI (2011-2023). This class for MIC values is a quite a special data type: formally it is an ordered \link{factor} with valid MIC values as \link{factor} levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers: \if{html}{\out{
}}\preformatted{x <- random_mic(10) x #> Class 'mic' #> [1] 16 1 8 8 64 >=128 0.0625 32 32 16 is.factor(x) #> [1] TRUE x[1] * 2 #> [1] 32 median(x) #> [1] 26 }\if{html}{\out{
}} This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using \link{numeric} values in data analysis, e.g.: \if{html}{\out{
}}\preformatted{x[x > 4] #> Class 'mic' #> [1] 16 8 8 64 >=128 32 32 16 df <- data.frame(x, hospital = "A") subset(df, x > 4) # or with dplyr: df \%>\% filter(x > 4) #> x hospital #> 1 16 A #> 5 64 A #> 6 >=128 A #> 8 32 A #> 9 32 A #> 10 16 A }\if{html}{\out{
}} All so-called \link[=groupGeneric]{group generic functions} are implemented for the MIC class (such as \code{!}, \code{!=}, \code{<}, \code{>=}, \code{\link[=exp]{exp()}}, \code{\link[=log2]{log2()}}). Some functions of the \code{stats} package are also implemented (such as \code{\link[=quantile]{quantile()}}, \code{\link[=median]{median()}}, \code{\link[=fivenum]{fivenum()}}). Since \code{\link[=sd]{sd()}} and \code{\link[=var]{var()}} are non-generic functions, these could not be extended. Use \code{\link[=mad]{mad()}} as an alternative, or use e.g. \code{sd(as.numeric(x))} where \code{x} is your vector of MIC values. Using \code{\link[=as.double]{as.double()}} or \code{\link[=as.numeric]{as.numeric()}} on MIC values will remove the operators and return a numeric vector. Do \strong{not} use \code{\link[=as.integer]{as.integer()}} on MIC values as by the \R convention on \link{factor}s, it will return the index of the factor levels (which is often useless for regular users). Use \code{\link[=droplevels]{droplevels()}} to drop unused levels. At default, it will return a plain factor. Use \code{droplevels(..., as.mic = TRUE)} to maintain the \code{mic} class. With \code{\link[=rescale_mic]{rescale_mic()}}, existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions. For \code{ggplot2}, use one of the \code{\link[=scale_x_mic]{scale_*_mic()}} functions to plot MIC values. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values. \code{NA_mic_} is a missing value of the new \code{mic} class, analogous to e.g. base \R's \code{\link[base:NA]{NA_character_}}. } \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/SIR values: as.mic("<=0.002; S") # mathematical processing treats MICs as numeric values fivenum(mic_data) quantile(mic_data) all(mic_data < 512) # limit MICs using rescale_mic() rescale_mic(mic_data, mic_range = c(4, 16)) # interpret MIC values as.sir( x = as.mic(2), mo = as.mo("Streptococcus pneumoniae"), ab = "AMX", guideline = "EUCAST" ) as.sir( 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") if (require("ggplot2")) { autoplot(mic_data, mo = "E. coli", ab = "cipro") } if (require("ggplot2")) { autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch } } \seealso{ \code{\link[=as.sir]{as.sir()}} } \keyword{datasets}