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DEsingle for detecting three types of differential expression in single-cell RNA-seq data

Bioconductor version: Release (3.18)

DEsingle is an R package for differential expression (DE) analysis of single-cell RNA-seq (scRNA-seq) data. It defines and detects 3 types of differentially expressed genes between two groups of single cells, with regard to different expression status (DEs), differential expression abundance (DEa), and general differential expression (DEg). DEsingle employs Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect the 3 types of DE genes. Results showed that DEsingle outperforms existing methods for scRNA-seq DE analysis, and can reveal different types of DE genes that are enriched in different biological functions.

Author: Zhun Miao <miaoz13 at tsinghua.org.cn>

Maintainer: Zhun Miao <miaoz13 at tsinghua.org.cn>

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biocViews DifferentialExpression, GeneExpression, ImmunoOncology, Preprocessing, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.22.0
In Bioconductor since BioC 3.7 (R-3.5) (6 years)
License GPL-2
Depends R (>= 3.4.0)
Imports stats, Matrix (>= 1.2-14), MASS (>= 7.3-45), VGAM (>= 1.0-2), bbmle (>= 1.0.18), gamlss (>= 4.4-0), maxLik (>= 1.3-4), pscl (>= 1.4.9), BiocParallel(>= 1.12.0)
System Requirements
URL https://miaozhun.github.io/DEsingle/
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Source Package DEsingle_1.22.0.tar.gz
Windows Binary DEsingle_1.22.0.zip
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