Create linear regression plot to show the expression the of top DEGs

plotDEGRegression(
  inSCE,
  useResult,
  threshP = FALSE,
  labelBy = NULL,
  nrow = 6,
  ncol = 6,
  defaultTheme = TRUE,
  isLogged = TRUE,
  check_sanity = TRUE
)

Arguments

inSCE: SingleCellExperiment inherited object.
useResult: character. A string specifying the analysisName used when running a differential expression analysis function.
threshP: logical. Whether to plot threshold values from adaptive thresholding, instead of using the assay used by when performing DE analysis. Default FALSE.
labelBy: A single character for a column of rowData(inSCE) as where to search for the labeling text. Default NULL.
nrow: Integer. Number of rows in the plot grid. Default 6.
ncol: Integer. Number of columns in the plot grid. Default 6.
defaultTheme: Logical scalar. Whether to use default SCTK theme in ggplot. Default TRUE.
isLogged: Logical scalar. Whether the assay used for the analysis is logged. If not, will do a log(assay + 1) transformation. Default TRUE.
check_sanity: Logical scalar. Whether to perform MAST's sanity check to see if the counts are logged. Default TRUE

Value

A ggplot object of linear regression

Details

Any of the differential expression analysis method from SCTK should be performed prior to using this function

Examples

data("sceBatches")
logcounts(sceBatches) <- log(counts(sceBatches) + 1)
sce.w <- subsetSCECols(sceBatches, colData = "batch == 'w'")
sce.w <- runWilcox(sce.w, class = "cell_type", classGroup1 = "alpha",
                   groupName1 = "w.alpha", groupName2 = "w.beta",
                   analysisName = "w.aVSb")
#> Tue Jun 28 22:04:10 2022 ... Running DE with wilcox, Analysis name: w.aVSb
plotDEGRegression(sce.w, "w.aVSb")