scPCA: Sparse Contrastive Principal Component Analysis

A toolbox for sparse contrastive principal component analysis (scPCA) of high-dimensional biological data. scPCA combines the stability and interpretability of sparse PCA with contrastive PCA's ability to disentangle biological signal from techical noise through the use of control data. Also implements and extends cPCA.

Package details

AuthorPhilippe Boileau [aut, cre, cph] (<https://orcid.org/0000-0002-4850-2507>), Nima Hejazi [aut] (<https://orcid.org/0000-0002-7127-2789>), Sandrine Dudoit [ctb, ths] (<https://orcid.org/0000-0002-6069-8629>)
Bioconductor views DifferentialExpression GeneExpression Microarray PrincipalComponent RNASeq Sequencing
MaintainerPhilippe Boileau <[email protected]>
LicenseMIT + file LICENSE
Version1.0.0
URL https://github.com/PhilBoileau/scPCA
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("scPCA")

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scPCA documentation built on Oct. 31, 2019, 7:53 a.m.