DESeq is a tool for hypothesis testing and differential gene expression analysis of RNA-seq data. The DESeq algorithm applies the negative binomial distribution and a Likelihood Ratio Test (LRT), it normalizes data by trimmed mean of M-values and circumvents a small sample size by incorporating information from all genes in a set of samples.
Gene expression; Transcriptomics
Anders S, Huber W "Differential expression analysis for sequence count data." Genome Biol. 2010;11(10):R106. https://doi.org/10.1186/gb-2010-11-10-r106
PMID: 20979621
PMCID: PMC3218662
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J1, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M "Orchestrating high-throughput genomic analysis with Bioconductor." Nat Methods. 2015 Feb;12(2):115-21. https://doi.org/10.1038/nmeth.3252
PMID: 25633503
PMCID: PMC4509590
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J. "Bioconductor: open software development for computational biology and bioinformatics." Genome Biol. 2004;5(10):R80. Epub 2004 Sep 15. https://doi.org/10.1186/gb-2004-5-10-r80
PMID: 15461798
PMCID: PMC545600
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