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

View source: R/utils_singlecell.R

sc_to_indicator_matrixR Documentation

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.