scrna_evalPlot_filtering {pipeComp} | R Documentation

## scrna_evalPlot_filtering

### 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)

[Package pipeComp version 1.0.0 Index]