scrna_evalPlot_filtering: scrna_evalPlot_filtering

In pipeComp: pipeComp pipeline benchmarking framework

Description

scrna_evalPlot_filtering

Usage

scrna_evalPlot_filtering(
  res,
  steps = c("doublet", "filtering"),
  clustMetric = "mean_F1",
  filterExpr = TRUE,
  atNearestK = FALSE,
  returnTable = FALSE,
  point.size = 2.2,
  ...
)

Arguments

res	Aggregated pipeline results (i.e. the output of 'runPipeline' or 'aggregateResults')
steps	Steps to include (default 'doublet' and 'filtering'); other steps will be averaged.
clustMetric	Clustering accuracy metric to use (default 'mean_F1“)
filterExpr	An optional filtering expression based on the columns of the clustering evaluation (e.g. 'filterExpr=param1=="value1"' or 'filterExpr=n_clus==true.nbClusts').
atNearestK	Logical; whether to restrict analyses to those giving the smallest deviation from the real number of clusters (default FALSE).
returnTable	Logical; whether to return the data rather than plot.
point.size	Size of the points
...	passed to 'geom_point'

Value

A ggplot, or a data.frame if 'returnTable=TRUE'

Examples

data("exampleResults", package="pipeComp")
scrna_evalPlot_filtering(exampleResults)

pipeComp documentation built on Nov. 8, 2020, 7:35 p.m.