{% set version = "1.10.0" %}
{% set name = "gcapc" %}
{% set bioc = "3.10" %}

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: 0db687d4176302902d1e0a63a77a8dab
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
  noarch: generic
# Suggests: BiocStyle, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm10
requirements:
  host:
    - 'bioconductor-biocgenerics >=0.32.0,<0.33.0'
    - 'bioconductor-biostrings >=2.54.0,<2.55.0'
    - 'bioconductor-bsgenome >=1.54.0,<1.55.0'
    - 'bioconductor-genomeinfodb >=1.22.0,<1.23.0'
    - 'bioconductor-genomicalignments >=1.22.0,<1.23.0'
    - 'bioconductor-genomicranges >=1.38.0,<1.39.0'
    - 'bioconductor-iranges >=2.20.0,<2.21.0'
    - 'bioconductor-rsamtools >=2.2.0,<2.3.0'
    - 'bioconductor-s4vectors >=0.24.0,<0.25.0'
    - r-base
    - r-mass
    - r-matrixstats
  run:
    - 'bioconductor-biocgenerics >=0.32.0,<0.33.0'
    - 'bioconductor-biostrings >=2.54.0,<2.55.0'
    - 'bioconductor-bsgenome >=1.54.0,<1.55.0'
    - 'bioconductor-genomeinfodb >=1.22.0,<1.23.0'
    - 'bioconductor-genomicalignments >=1.22.0,<1.23.0'
    - 'bioconductor-genomicranges >=1.38.0,<1.39.0'
    - 'bioconductor-iranges >=2.20.0,<2.21.0'
    - 'bioconductor-rsamtools >=2.2.0,<2.3.0'
    - 'bioconductor-s4vectors >=0.24.0,<0.25.0'
    - r-base
    - r-mass
    - r-matrixstats
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: GPL-3
  summary: 'GC Aware Peak Caller'
  description: 'Peak calling for ChIP-seq data with consideration of potential GC bias in sequencing reads. GC bias is first estimated with generalized linear mixture models using effective GC strategy, then applied into peak significance estimation.'
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

