{% set version = "1.40.0" %}
{% set name = "GSVA" %}
{% set bioc = "3.13" %}

package:
  name: 'bioconductor-{{ name|lower }}'
  version: '{{ version }}'
source:
  url:
    - 'https://bioconductor.org/packages/{{ bioc }}/bioc/src/contrib/{{ name }}_{{ version }}.tar.gz'
    - 'https://bioarchive.galaxyproject.org/{{ name }}_{{ version }}.tar.gz'
    - 'https://depot.galaxyproject.org/software/bioconductor-{{ name|lower }}/bioconductor-{{ name|lower }}_{{ version }}_src_all.tar.gz'
  md5: eacba3827f5acb19de133656e00a895b
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
# Suggests: BiocGenerics, RUnit, BiocStyle, knitr, rmarkdown, limma, RColorBrewer, org.Hs.eg.db, genefilter, edgeR, GSVAdata, shiny, shinydashboard, ggplot2, data.table, plotly, future, promises, shinybusy, shinyjs
requirements:
  host:
    - 'bioconductor-biobase >=2.52.0,<2.53.0'
    - 'bioconductor-biocparallel >=1.26.0,<1.27.0'
    - 'bioconductor-biocsingular >=1.8.0,<1.9.0'
    - 'bioconductor-delayedarray >=0.18.0,<0.19.0'
    - 'bioconductor-delayedmatrixstats >=1.14.0,<1.15.0'
    - 'bioconductor-gseabase >=1.54.0,<1.55.0'
    - 'bioconductor-hdf5array >=1.20.0,<1.21.0'
    - 'bioconductor-iranges >=2.26.0,<2.27.0'
    - 'bioconductor-s4vectors >=0.30.0,<0.31.0'
    - 'bioconductor-singlecellexperiment >=1.14.0,<1.15.0'
    - 'bioconductor-sparsematrixstats >=1.4.0,<1.5.0'
    - 'bioconductor-summarizedexperiment >=1.22.0,<1.23.0'
    - r-base
    - r-matrix
    - libblas
    - liblapack
  run:
    - 'bioconductor-biobase >=2.52.0,<2.53.0'
    - 'bioconductor-biocparallel >=1.26.0,<1.27.0'
    - 'bioconductor-biocsingular >=1.8.0,<1.9.0'
    - 'bioconductor-delayedarray >=0.18.0,<0.19.0'
    - 'bioconductor-delayedmatrixstats >=1.14.0,<1.15.0'
    - 'bioconductor-gseabase >=1.54.0,<1.55.0'
    - 'bioconductor-hdf5array >=1.20.0,<1.21.0'
    - 'bioconductor-iranges >=2.26.0,<2.27.0'
    - 'bioconductor-s4vectors >=0.30.0,<0.31.0'
    - 'bioconductor-singlecellexperiment >=1.14.0,<1.15.0'
    - 'bioconductor-sparsematrixstats >=1.4.0,<1.5.0'
    - 'bioconductor-summarizedexperiment >=1.22.0,<1.23.0'
    - r-base
    - r-matrix
  build:
    - {{ compiler('c') }}
    - make
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: 'GPL (>= 2)'
  summary: 'Gene Set Variation Analysis for microarray and RNA-seq data'
  description: '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.'
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'
extra:
  identifiers:
    - biotools:gsva
  parent_recipe:
    name: bioconductor-gsva
    path: recipes/bioconductor-gsva
    version: 1.28.0

