#' Unsupervised random forest MDS plot
#' @rdname plotUnsupervisedRF
#' @description A multidimensional scaling (MDS) plot of unsupervised random forest analysis
#' @param x object of class `AnalysisData` or `Analysis`
#' @param cls sample information column to use for sample labelling
#' @param rf list of additional parameters to pass to `randomForest`
#' @param label info column to use for sample labels. Set to NULL for no labels.
#' @param shape TRUE/FALSE use shape aesthetic for plot points.
#' Defaults to TRUE when the number of classes is greater than 12
#' @param ellipses TRUE/FALSE, plot multivariate normal distribution 95%
#' confidence ellipses for each class
#' @param seed random number seed
#' @param title plot title
#' @param legendPosition legend position to pass to legend.position argument
#' of `ggplot2::theme`. Set to "none" to remove legend.
#' @param labelSize label size. Ignored if `label` is `NULL`
#' @param type `raw` or `pre-treated` data to plot
#' @param ... arguments to pass to the appropriate method
#' @examples
#' library(metaboData)
#'
#' d <- analysisData(abr1$neg[,200:300],abr1$fact)
#'
#' ## Unsupervised random forest MDS plot
#' plotUnsupervisedRF(d,cls = 'day')
#' @export
setGeneric('plotUnsupervisedRF',
function(
x,
cls = 'class',
rf = list(),
label = NULL,
shape = FALSE,
ellipses = TRUE,
seed = 1234,
title = '',
legendPosition = 'bottom',
labelSize = 2,
...)
standardGeneric('plotUnsupervisedRF'))
#' @rdname plotUnsupervisedRF
#' @importFrom stats cmdscale
setMethod('plotUnsupervisedRF',
signature = 'AnalysisData',
function(x,
cls = 'class',
rf = list(),
label = NULL,
shape = FALSE,
ellipses = TRUE,
seed = 1234,
title = '',
legendPosition = 'bottom',
labelSize = 2){
rf <- randomForest(x,
cls = NULL,
rf = rf,
reps = 1,
seed = seed)
plotMDS(rf,
cls = cls,
label = label,
shape = shape,
ellipses = ellipses,
title = title,
legendPosition = legendPosition,
labelSize = labelSize)
}
)
#' @rdname plotUnsupervisedRF
setMethod('plotUnsupervisedRF',
signature = 'Analysis',
function(x,
cls = 'class',
rf = list(),
label = NULL,
shape = FALSE,
ellipses = TRUE,
seed = 1234,
title = '',
legendPosition = 'bottom',
labelSize = 2,
type = c('pre-treated','raw')){
type <- match.arg(
type,
choices = c(
'pre-treated',
'raw'
)
)
if (type == 'pre-treated') {
d <- x %>%
preTreated()
}
if (type == 'raw'){
d <- x %>%
raw()
}
plotUnsupervisedRF(d,
cls = cls,
rf = rf,
label = label,
shape = shape,
ellipses = ellipses,
seed = seed,
title = title,
legendPosition = legendPosition,
labelSize = labelSize)
}
)
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