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DESeq2: Differential gene expression analysis based on the ...

Package DESeq2 May 16, 2023 TypePackageTitleDifferential gene expression analysis based on the negativebinomial variance-mean dependence in count data fromhigh-throughput sequencing assays and test for differentialexpression based on a model using the negative (>= 3)VignetteBuilderknitr, rmarkdownImportsBiocGenerics (>= ), Biobase, BiocParallel, matrixStats,methods, stats4, locfit, ggplot2, Rcpp (>= )DependsS4 Vectors (>= ), IRanges, GenomicRanges,SummarizedExperiment (>= )Suggeststestthat, knitr, rmarkdown, vsn, pheatmap, RColorBrewer,apeglm, ashr, tximport, tximeta, tximportData, readr, pbapply,airway, pasilla (>= ), glmGamPoi, BiocManagerLinkingToRcpp, , RNASeq, ChIPSeq, GeneExpression, Transcription,Normalization, DifferentialExpression, Bayesian, Regression,PrincipalComponent, Clustering, documented:AuthorMichael Love [aut, cre],Constantin Ahlmann-Eltze [ctb],Kwame Forbes [ctb],Simon Anders [aut, ctb],Wolfgang Huber [aut, ctb],RADIANT EU FP7 [fnd],NIH NHGRI [fnd],CZI [fnd]Rtopics documented:DESeq2-package.

Package ‘DESeq2’ January 20, 2022 Type Package Title Differential gene expression analysis based on the negative binomial distribution Version 1.34.0

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  Based, Analysis, Distribution, Differential, Gene, Expression, Negative, Binomial, Differential gene expression analysis based, Differential gene expression analysis based on the negative binomial distribution

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