sc_to_indicator_matrix: Calculates differentially expressed genes from single cell...

In baumbachlab/keypathwayminer-R: KeyPathwayMiner R-Package

Calculates differentially expressed genes from single cell object

Description

Calculates differentially expressed genes between multiple groups with reference to a control group using a hurdle model tailored to scRNA-seq data

Usage

sc_to_indicator_matrix(
  sc_obj,
  covarariate,
  referenceGroup,
  saveSummary = TRUE,
  summaryName = NULL,
  designFormula = NULL,
  FCThreshold = 2,
  pvalueThreshold = 0.05,
  nameIndicatorMatrix = NULL
)

Arguments

sc_obj	single cell object of type seurat, singleCellAssay or singlCellExperiment
covarariate	colname of metadata with groups for differential expression
referenceGroup	reference/control group
saveSummary	if TRUE saves the result of the differential analysis as a .rds file
summaryName	name of the rds file if saveSummary=TRUE
designFormula	string which will be used as formula in MAST's zlm function
FCThreshold	Threshold of log 2 fold change
pvalueThreshold	p value cut off after FDR correction for differentially expressed genes
nameIndicatorMatrix	indicator matrix which can be used for kpm() execution

Details

To use this method, MAST has to be installed (see https://github.com/RGLab/MAST/ )

Value

dataframe of of putative differentially expressed genes

References

Andrew McDavid, Greg Finak and Masanao Yajima (2017). MAST: Model-based Analysis of Single Cell Transcriptomics. R package version 1.2.1. https://github.com/RGLab/MAST/

baumbachlab/keypathwayminer-R documentation built on June 29, 2023, 11:21 a.m.