{% set version = "1.28.0" %}
{% set name = "trigger" %}
{% set bioc = "3.8" %}

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 }}/bioconductor-{{ name }}_{{ version }}_src_all.tar.gz'
  md5: 26b0b707b709215845adcd78059c142f
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
requirements:
  host:
    - 'bioconductor-qvalue >=2.14.0,<2.15.0'
    - 'bioconductor-sva >=3.30.0,<3.31.0'
    - r-base
    - r-corpcor
    - r-qtl
  run:
    - 'bioconductor-qvalue >=2.14.0,<2.15.0'
    - 'bioconductor-sva >=3.30.0,<3.31.0'
    - r-base
    - r-corpcor
    - r-qtl
  build:
    - {{ compiler('c') }}
    - make
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: GPL-3
  summary: 'This R package provides tools for the statistical analysis of integrative genomic data that involve some combination of: genotypes, high-dimensional intermediate traits (e.g., gene expression, protein abundance), and higher-order traits (phenotypes). The package includes functions to: (1) construct global linkage maps between genetic markers and gene expression; (2) analyze multiple-locus linkage (epistasis) for gene expression; (3) quantify the proportion of genome-wide variation explained by each locus and identify eQTL hotspots; (4) estimate pair-wise causal gene regulatory probabilities and construct gene regulatory networks; and (5) identify causal genes for a quantitative trait of interest.'
extra:
  identifiers:
    - biotools:trigger
    - doi:10.1038/nmeth.3252
  parent_recipe:
    name: bioconductor-trigger
    path: recipes/bioconductor-trigger
    version: 1.26.0

