{% set version = "1.22.0" %}
{% set name = "ChIPanalyser" %}
{% set bioc = "3.17" %}

package:
  name: 'bioconductor-{{ name|lower }}'
  version: '{{ version }}'
source:
  url:
    - 'https://bioconductor.org/packages/{{ bioc }}/bioc/src/contrib/{{ name }}_{{ version }}.tar.gz'
    - 'https://bioconductor.org/packages/{{ bioc }}/bioc/src/contrib/Archive/{{ name }}/{{ 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: 75932168cfbb3bf4013b82f2cf95bf97
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
  noarch: generic
# Suggests: BSgenome.Dmelanogaster.UCSC.dm6,knitr, RUnit, BiocGenerics
requirements:
  host:
    - 'bioconductor-biostrings >=2.68.0,<2.69.0'
    - 'bioconductor-bsgenome >=1.68.0,<1.69.0'
    - 'bioconductor-genomeinfodb >=1.36.0,<1.37.0'
    - 'bioconductor-genomicranges >=1.52.0,<1.53.0'
    - 'bioconductor-iranges >=2.34.0,<2.35.0'
    - 'bioconductor-rtracklayer >=1.60.0,<1.61.0'
    - 'bioconductor-s4vectors >=0.38.0,<0.39.0'
    - r-base
    - r-biocmanager
    - r-rcolorbrewer
    - r-rcpproll
    - r-rocr
  run:
    - 'bioconductor-biostrings >=2.68.0,<2.69.0'
    - 'bioconductor-bsgenome >=1.68.0,<1.69.0'
    - 'bioconductor-genomeinfodb >=1.36.0,<1.37.0'
    - 'bioconductor-genomicranges >=1.52.0,<1.53.0'
    - 'bioconductor-iranges >=2.34.0,<2.35.0'
    - 'bioconductor-rtracklayer >=1.60.0,<1.61.0'
    - 'bioconductor-s4vectors >=0.38.0,<0.39.0'
    - r-base
    - r-biocmanager
    - r-rcolorbrewer
    - r-rcpproll
    - r-rocr
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: GPL-3
  summary: 'ChIPanalyser: Predicting Transcription Factor Binding Sites'
  description: 'ChIPanalyser is a package to predict and understand TF binding by utilizing a statistical thermodynamic model. The model incorporates 4 main factors thought to drive TF binding: Chromatin State, Binding energy, Number of bound molecules and a scaling factor modulating TF binding affinity. Taken together, ChIPanalyser produces ChIP-like profiles that closely mimic the patterns seens in real ChIP-seq data.'
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

