swMATH ID: 41938
Software Authors: Michael Love, Constantin Ahlmann-Eltze, Kwame Forbes, Simon Anders, Wolfgang Huber
Description: R/Bioconductor package DESeq2: Differential gene expression analysis based on the negative binomial distribution. Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution. Citation (from within R, enter citation(”DESeq2”)): Love MI, Huber W, Anders S (2014). “Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.” Genome Biology, 15, 550. doi: 10.1186/s13059-014-0550-8.
Homepage: https://bioconductor.org/packages/release/bioc/html/DESeq2.html
Dependencies: R
Related Software: Bioconductor; edgeR; R; DEseq; Voom; BaySeq; ShrinkBayes; gcrma; ZIFA; EBSeq; limma; zinbwave; CRAN; Phyloseq; MAST; KEGG; UMAP; CIDR; SC3; glmnet
Referenced in: 26 Publications

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