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Gene Expression Variation Analysis (GEVA)

Bioconductor version: Release (3.18)

Statistic methods to evaluate variations of differential expression (DE) between multiple biological conditions. It takes into account the fold-changes and p-values from previous differential expression (DE) results that use large-scale data (*e.g.*, microarray and RNA-seq) and evaluates which genes would react in response to the distinct experiments. This evaluation involves an unique pipeline of statistical methods, including weighted summarization, quantile detection, cluster analysis, and ANOVA tests, in order to classify a subset of relevant genes whose DE is similar or dependent to certain biological factors.

Author: Itamar José Guimarães Nunes [aut, cre] , Murilo Zanini David [ctb], Bruno César Feltes [ctb] , Marcio Dorn [ctb]

Maintainer: Itamar José Guimarães Nunes <nunesijg at gmail.com>

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Reference Manual PDF


biocViews Classification, DifferentialExpression, GeneExpression, Microarray, MultipleComparison, RNASeq, Software, SystemsBiology, Transcriptomics
Version 1.10.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License LGPL-3
Depends R (>= 4.1)
Imports grDevices, graphics, methods, stats, utils, dbscan, fastcluster, matrixStats
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URL https://github.com/sbcblab/geva
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Suggests devtools, knitr, rmarkdown, roxygen2, limma, topGO, testthat (>= 3.0.0)
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Follow Installation instructions to use this package in your R session.

Source Package geva_1.10.0.tar.gz
Windows Binary geva_1.10.0.zip
macOS Binary (x86_64) geva_1.10.0.tgz
macOS Binary (arm64) geva_1.10.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/geva
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/geva
Bioc Package Browser https://code.bioconductor.org/browse/geva/
Package Short Url https://bioconductor.org/packages/geva/
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