runScanpyFindMarkers: runScanpyFindMarkers

In compbiomed/singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

runScanpyFindMarkers

Description

runScanpyFindMarkers

Usage

runScanpyFindMarkers(
  inSCE,
  nGenes = NULL,
  useAssay = "scanpyNormData",
  colDataName,
  group1 = "all",
  group2 = "rest",
  test = c("wilcoxon", "t-test", "t-test_overestim_var", "logreg"),
  corr_method = c("benjamini-hochberg", "bonferroni")
)

Arguments

inSCE	Input SingleCellExperiment object.
nGenes	The number of genes that appear in the returned tables. Defaults to all genes.
useAssay	Specify the name of the assay to use for computation of marker genes. It is recommended to use log normalized assay.
colDataName	colData to use as the key of the observations grouping to consider.
group1	Name of group1. Subset of groups, to which comparison shall be restricted, or 'all' (default), for all groups.
group2	Name of group2. If 'rest', compare each group to the union of the rest of the group. If a group identifier, compare with respect to this group. Default is 'rest'
test	Test to use for DE. Default "t-test".
corr_method	p-value correction method. Used only for 't-test', 't-test_overestim_var', and 'wilcoxon'.

Value

A SingleCellExperiment object that contains marker genes populated in a data.frame stored inside metadata slot.

Examples

data(scExample, package = "singleCellTK")
## Not run: 
sce <- runScanpyNormalizeData(sce, useAssay = "counts")
sce <- runScanpyFindHVG(sce, useAssay = "scanpyNormData", method = "seurat")
sce <- runScanpyScaleData(sce, useAssay = "scanpyNormData")
sce <- runScanpyPCA(sce, useAssay = "scanpyScaledData")
sce <- runScanpyFindClusters(sce, useReducedDim = "scanpyPCA")
sce <- runScanpyFindMarkers(sce, colDataName = "Scanpy_louvain_1" )

## End(Not run)

compbiomed/singleCellTK documentation built on Oct. 27, 2024, 3:26 a.m.