Seurat (version 2.3.3)

MASTDETest: Differential expression using MAST

Description

Identifies differentially expressed genes between two groups of cells using a hurdle model tailored to scRNA-seq data. Utilizes the MAST package to run the DE testing.

Usage

MASTDETest(object, cells.1, cells.2, genes.use = NULL, latent.vars = NULL,
  assay.type = "RNA", ...)

Arguments

object

Seurat object

cells.1

Group 1 cells

cells.2

Group 2 cells

genes.use

Genes to use for test

latent.vars

Confounding variables to adjust for in DE test. Default is "nUMI", which adjusts for cellular depth (i.e. cellular detection rate). For non-UMI based data, set to nGene instead.

assay.type

Type of assay to fetch data for (default is RNA)

…

Additional parameters to zero-inflated regression (zlm) function in MAST

Value

Returns a p-value ranked matrix of putative differentially expressed genes.

Details

To use this method, please install MAST, using instructions at https://github.com/RGLab/MAST/

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/

Examples

# NOT RUN {
  pbmc_small
  MASTDETest(pbmc_small, cells.1 = WhichCells(object = pbmc_small, ident = 1),
              cells.2 = WhichCells(object = pbmc_small, ident = 2))
# }
# NOT RUN {
# }