- recipe bioconductor-gsva
Gene Set Variation Analysis for microarray and RNA-seq data
- Homepage
- License
GPL (>= 2)
- Recipe
- Links
biotools: gsva
Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.
- package bioconductor-gsva¶
-
- Versions
1.42.0-1
,1.42.0-0
,1.40.0-0
,1.38.2-0
,1.38.0-0
,1.36.0-0
,1.34.0-0
,1.32.0-1
,1.30.0-1
,1.42.0-1
,1.42.0-0
,1.40.0-0
,1.38.2-0
,1.38.0-0
,1.36.0-0
,1.34.0-0
,1.32.0-1
,1.30.0-1
,1.30.0-0
,1.28.0-0
,1.26.0-0
,1.24.2-0
,1.24.1-0
- Depends
bioconductor-biobase
>=2.54.0,<2.55.0
bioconductor-biocparallel
>=1.28.0,<1.29.0
bioconductor-biocsingular
>=1.10.0,<1.11.0
bioconductor-delayedarray
>=0.20.0,<0.21.0
bioconductor-delayedmatrixstats
>=1.16.0,<1.17.0
bioconductor-gseabase
>=1.56.0,<1.57.0
bioconductor-hdf5array
>=1.22.0,<1.23.0
bioconductor-iranges
>=2.28.0,<2.29.0
bioconductor-s4vectors
>=0.32.0,<0.33.0
bioconductor-singlecellexperiment
>=1.16.0,<1.17.0
bioconductor-sparsematrixstats
>=1.6.0,<1.7.0
bioconductor-summarizedexperiment
>=1.24.0,<1.25.0
libblas
>=3.8.0,<4.0a0
libgcc-ng
>=10.3.0
liblapack
>=3.8.0,<4.0a0
r-base
>=4.1,<4.2.0a0
- Required By
Installation
With an activated Bioconda channel (see 2. Set up channels), install with:
conda install bioconductor-gsva
and update with:
conda update bioconductor-gsva
or use the docker container:
docker pull quay.io/biocontainers/bioconductor-gsva:<tag>
(see bioconductor-gsva/tags for valid values for
<tag>
)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-gsva/README.html)