# This file created by conda-build 3.21.4
# meta.yaml template originally from:
# /opt/recipe, last modified Thu Jun  3 18:50:38 2021
# ------------------------------------------------

package:
  name: bioconductor-gsva
  version: 1.40.0
source:
  md5: eacba3827f5acb19de133656e00a895b
  url:
    - https://bioarchive.galaxyproject.org/GSVA_1.40.0.tar.gz
    - https://bioconductor.org/packages/3.13/bioc/src/contrib/GSVA_1.40.0.tar.gz
    - https://depot.galaxyproject.org/software/bioconductor-gsva/bioconductor-gsva_1.40.0_src_all.tar.gz
build:
  number: '0'
  rpaths:
    - lib/
    - lib/R/lib/
  string: r41hd029910_0
requirements:
  build:
    - _libgcc_mutex 0.1 conda_forge
    - _openmp_mutex 4.5 1_gnu
    - binutils_impl_linux-64 2.35.1 h193b22a_2
    - binutils_linux-64 2.35 h67ddf6f_30
    - gcc_impl_linux-64 9.3.0 h70c0ae5_19
    - gcc_linux-64 9.3.0 hf25ea35_30
    - kernel-headers_linux-64 2.6.32 h77966d4_13
    - ld_impl_linux-64 2.35.1 hea4e1c9_2
    - libgcc-devel_linux-64 9.3.0 h7864c58_19
    - libgcc-ng 9.3.0 h2828fa1_19
    - libgomp 9.3.0 h2828fa1_19
    - libstdcxx-ng 9.3.0 h6de172a_19
    - make 4.3 hd18ef5c_1
    - sysroot_linux-64 2.12 h77966d4_13
  host:
    - _libgcc_mutex 0.1 conda_forge
    - _openmp_mutex 4.5 1_gnu
    - _r-mutex 1.0.1 anacondar_1
    - binutils_impl_linux-64 2.35.1 h193b22a_2
    - binutils_linux-64 2.35 h67ddf6f_30
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    - bioconductor-biostrings 2.60.0 r41hd029910_0
    - bioconductor-delayedarray 0.18.0 r41hd029910_0
    - bioconductor-delayedmatrixstats 1.14.0 r41hdfd78af_0
    - bioconductor-genomeinfodb 1.28.0 r41hdfd78af_0
    - bioconductor-genomeinfodbdata 1.2.6 r41hdfd78af_0
    - bioconductor-genomicranges 1.44.0 r41hd029910_0
    - bioconductor-graph 1.70.0 r41hd029910_0
    - bioconductor-gseabase 1.54.0 r41hdfd78af_0
    - bioconductor-hdf5array 1.20.0 r41hd029910_0
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    - bioconductor-keggrest 1.32.0 r41hdfd78af_0
    - bioconductor-matrixgenerics 1.4.0 r41hdfd78af_0
    - bioconductor-rhdf5 2.36.0 r41h399db7b_0
    - bioconductor-rhdf5filters 1.4.0 r41h399db7b_0
    - bioconductor-rhdf5lib 1.14.0 r41hd029910_0
    - bioconductor-s4vectors 0.30.0 r41hd029910_0
    - bioconductor-scaledmatrix 1.0.0 r41hdfd78af_0
    - bioconductor-singlecellexperiment 1.14.1 r41hdfd78af_0
    - bioconductor-sparsematrixstats 1.4.0 r41h399db7b_0
    - bioconductor-summarizedexperiment 1.22.0 r41hdfd78af_0
    - bioconductor-xvector 0.32.0 r41hd029910_0
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    - lerc 2.2.1 h9c3ff4c_0
    - libblas 3.8.0 11_h86c2bf4_netlib
    - libcblas 3.8.0 11_h86c2bf4_netlib
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    - pcre2 10.36 h032f7d1_1
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    - r-askpass 1.1 r41hcfec24a_2
    - r-base 4.1.0 h9e01966_1
    - r-bh 1.75.0_0 r41hc72bb7e_0
    - r-bit 4.0.4 r41hcfec24a_0
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    - r-formatr 1.11 r41hc72bb7e_0
    - r-futile.logger 1.4.3 r41hc72bb7e_1003
    - r-futile.options 1.0.1 r41hc72bb7e_1002
    - r-glue 1.4.2 r41hcfec24a_0
    - r-httr 1.4.2 r41hc72bb7e_0
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    - readline 8.1 h46c0cb4_0
    - sed 4.8 he412f7d_0
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    - xorg-libxt 1.2.1 h7f98852_2
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    - xz 5.2.5 h516909a_1
    - zlib 1.2.11 h516909a_1010
    - zstd 1.5.0 ha95c52a_0
  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
    - libblas >=3.8.0,<4.0a0
    - libgcc-ng >=9.3.0
    - liblapack >=3.8.0,<4.0a0
    - r-base >=4.1,<4.2.0a0
    - r-matrix
test:
  commands:
    - $R -e "library('GSVA')"
about:
  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.
  home: https://bioconductor.org/packages/3.13/bioc/html/GSVA.html
  license: GPL (>= 2)
  license_file: /opt/conda/conda-bld/bioconductor-gsva_1622764589425/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/R/share/licenses/GPL-3
  summary: Gene Set Variation Analysis for microarray and RNA-seq data
extra:
  copy_test_source_files: true
  final: true
  identifiers:
    - biotools:gsva
