{ "_id": "6a3398963efcd9bda43a3d57", "Package": "GSVA", "Version": "2.6.2", "Title": "Gene Set Variation Analysis for Microarray and RNA-Seq Data", "Authors@R": "c(person(\"Robert\", \"Castelo\", role=c(\"aut\", \"cre\"),\ncomment=c(ORCID=\"0000-0003-2229-4508\"),\nemail=\"robert.castelo@upf.edu\"),\nperson(\"Justin\", \"Guinney\", role=\"aut\", email=\"jguinney@gmail.com\"),\nperson(\"Alexey\", \"Sergushichev\", role=\"ctb\", email=\"alsergbox@gmail.com\"),\nperson(\"Pablo Sebastian\", \"Rodriguez\", role=\"ctb\", email=\"pablo.rodriguez.bio2@gmail.com\"),\nperson(\"Axel\", \"Klenk\", role=\"ctb\", email=\"axel.klenk@gmail.com\"),\nperson(\"Chan Zuckerberg Initiative (CZI)\", role=\"fnd\"),\nperson(\"Spanish Ministry of Science, Innovation and Universities (MCIU)\", role=\"fnd\"))", "Description": "Gene Set Variation Analysis (GSVA) is a non-parametric,\nunsupervised method for estimating variation of gene set\nenrichment through the samples of a expression data set. GSVA\nperforms a change in coordinate systems, transforming the data\nfrom a gene by sample matrix to a gene-set by sample matrix,\nthereby allowing the evaluation of pathway enrichment for each\nsample. 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