DESingleTest: Differential expression using DEsingle
In Coolgenome/iTALK: Characterize and Illustrate Intercellular Communication

Description Usage Arguments Details Value References

Identifies differentially expressed genes between two groups of cells using DEsingle

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DESingleTest(sub_data, min_gene_expressed, min_valid_cells,
  contrast = unique(sub_data$compare_group), parallel = FALSE,
  BPPARAM = bpparam())

`sub_data`	Count data removed cell_type and selected certain two compare_group
`min_gene_expressed`	Genes expressed in minimum number of cells
`min_valid_cells`	Minimum number of genes detected in the cell
`contrast`	String vector specifying the contrast to be tested against the log2-fold-change threshold
`parallel`	If FALSE (default), no parallel computation is used; if TRUE, parallel computation using `BiocParallel`, with argument `BPPARAM`.
`BPPARAM`	An optional parameter object passed internally to `bplapply` when `parallel=TRUE`. If not specified, `bpparam()` (default) will be used.

This test does not support pre-processed genes. To use this method, please install DEsingle, using the instructions at https://github.com/miaozhun/DEsingle

A matrix of differentially expressed genes and related statistics.

Zhun Miao, Ke Deng, Xiaowo Wang, Xuegong Zhang (2018). DEsingle for detecting three types of differential expression in single-cell RNA-seq data. Bioinformatics, bty332. 10.1093/bioinformatics/bty332.

Coolgenome/iTALK documentation built on Aug. 3, 2019, 3:12 p.m.