limma Linear Models for Microarray and RNA-Seq Data …
Liu, R, Holik, AZ, Su, S, Jansz, N, Chen, K, Leong, HS, Blewitt, ME, Asselin-Labat, M-L, Smyth, GK, Ritchie, ME (2015). Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Nucleic Acids Research 43, e97. Law et al (2014) describe the voom and limma-trend pipelines for RNA-seq, while Liu et al (2015)
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Package ‘wateRmelon’ - Bioconductor - Home
www.bioconductor.orgPackage ‘wateRmelon’ November 17, 2018 Type Package Title Illumina 450 methylation array normalization and metrics Version 1.26.0 Author Leonard C Schalkwyk, Ruth Pidsley, Chloe CY Wong, with functions con-
limma Linear Models for Microarray and RNA-Seq Data User’s ...
www.bioconductor.orgFunctions for reading and pre-processing expression data from Illumina BeadChips were intro-duced in limma 3.0.0. See the case study in Section 17.3 for an example of these. Limma can also be used in conjunction with the vst or beadarray packages for pre-processing Illumina data.
DESeq2: Differential gene expression analysis based on the ...
www.bioconductor.orgPackage ‘DESeq2’ January 20, 2022 Type Package Title Differential gene expression analysis based on the negative binomial distribution Version 1.34.0
edgeR: differential analysis of sequence read count data ...
www.bioconductor.org2.15Gene set testing.....25 2.16Clustering, heatmaps etc ... MD, and Smyth, GK (2008). Small sample estimation of negative binomial dis-persion,withapplicationstoSAGEdata. Biostatistics 9,321–332. ... All other questions or problems concerning edgeR should be …
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