The DESeq2 package is designed for normalization, visualization, and differential analysis of high-dimensional count data. It makes use of empirical Bayes techniques to estimate priors for log fold change and dispersion, and to calculate posterior estimates for these quantities.
The main functions are:
DESeqDataSet - build the dataset, see tximeta & tximport packages for preparing input
DESeq - perform differential analysis
results - build a results table
lfcShrink - estimate shrunken LFC (posterior estimates) using apeglm & ashr pakges
vst - apply variance stabilizing transformation, e.g. for PCA or sample clustering
For detailed information on usage, see the package vignette, by typing
vignette("DESeq2"), or the workflow linked to on the first page
of the vignette.
All software-related questions should be posted to the Bioconductor Support Site:
The code can be viewed at the GitHub repository, which also lists the contributor code of conduct:
Michael Love, Wolfgang Huber, Simon Anders
Love, M.I., Huber, W., Anders, S. (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15:550. https://doi.org/10.1186/s13059-014-0550-8
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