{% set version = "1.30.0" %}
{% set name = "ALDEx2" %}
{% set bioc = "3.16" %}

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: 176a430e5a6cf5da2530c59ee4f69fbf
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
  noarch: generic
# Suggests: testthat, BiocStyle, knitr, rmarkdown
requirements:
  host:
    - 'bioconductor-biocparallel >=1.32.0,<1.33.0'
    - 'bioconductor-genomicranges >=1.50.0,<1.51.0'
    - 'bioconductor-iranges >=2.32.0,<2.33.0'
    - 'bioconductor-multtest >=2.54.0,<2.55.0'
    - 'bioconductor-s4vectors >=0.36.0,<0.37.0'
    - 'bioconductor-summarizedexperiment >=1.28.0,<1.29.0'
    - r-base
    - r-rfast
    - r-zcompositions
  run:
    - 'bioconductor-biocparallel >=1.32.0,<1.33.0'
    - 'bioconductor-genomicranges >=1.50.0,<1.51.0'
    - 'bioconductor-iranges >=2.32.0,<2.33.0'
    - 'bioconductor-multtest >=2.54.0,<2.55.0'
    - 'bioconductor-s4vectors >=0.36.0,<0.37.0'
    - 'bioconductor-summarizedexperiment >=1.28.0,<1.29.0'
    - r-base
    - r-rfast
    - r-zcompositions
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: 'GPL (>= 3)'
  summary: 'Analysis Of Differential Abundance Taking Sample Variation Into Account'
  description: 'A differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcoxon Rank Sum test and Welch''s t-test (via aldex.ttest), a Kruskal-Wallis test (via aldex.kw), a generalized linear model (via aldex.glm), or a correlation test (via aldex.corr). All tests report p-values and Benjamini-Hochberg corrected p-values. ALDEx2 also calculates expected standardized effect sizes for paired or unpaired study designs.'
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'
extra:
  identifiers:
    - biotools:aldex2
  parent_recipe:
    name: bioconductor-aldex2
    path: recipes/bioconductor-aldex2
    version: 1.12.0

