geva
Gene Expression Variation Analysis (GEVA)
Bioconductor version: 3.23 · Package version: 1.20.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("geva")Details
| Maintainer | Itamar José Guimarães Nunes <nunesijg@gmail.com> |
| Author | Itamar José Guimarães Nunes [aut, cre] (ORCID: <https://orcid.org/0000-0002-6246-4658>), Murilo Zanini David [ctb], Bruno César Feltes [ctb] (ORCID: <https://orcid.org/0000-0002-2825-8295>), Marcio Dorn [ctb] (ORCID: <https://orcid.org/0000-0001-8534-3480>) |
| License | LGPL-3 |
| URL | https://github.com/sbcblab/geva |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | Classification, DifferentialExpression, GeneExpression, Microarray, MultipleComparison, RNASeq, Software, SystemsBiology, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/geva/ |
Citation
From within R, enter citation("geva"):
Itamar José Guimarães Nunes. geva: Gene Expression Variation Analysis (GEVA). doi:10.18129/B9.bioc.geva, R package version 1.20.0, https://bioconductor.org/packages/geva.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | geva_1.20.0.tar.gz |
| Windows binary (x86_64) | geva_1.20.0.zip |
| macOS binary (arm64) | geva_1.20.0.tgz |
| macOS binary (x86_64) | geva_1.20.0.tgz |
Dependencies
Depends: R (>= 4.1)
Imports: grDevices, graphics, methods, stats, utils, dbscan, fastcluster, matrixStats
Suggests: devtools, knitr, rmarkdown, roxygen2, limma, topGO, testthat (>= 3.0.0)