View source: R/utils_singlecell.R
sc_to_indicator_matrix | R Documentation |
Calculates differentially expressed genes between multiple groups with reference to a control group using a hurdle model tailored to scRNA-seq data
sc_to_indicator_matrix(
sc_obj,
covarariate,
referenceGroup,
saveSummary = TRUE,
summaryName = NULL,
designFormula = NULL,
FCThreshold = 2,
pvalueThreshold = 0.05,
nameIndicatorMatrix = NULL
)
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 |
To use this method, MAST has to be installed (see https://github.com/RGLab/MAST/ )
dataframe of of putative differentially expressed genes
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/
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