{% set version = "1.4.0" %}
{% set name = "seqArchR" %}
{% 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: fecd57059a333de35b3509909921541c
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
  noarch: generic
# Suggests: cowplot, hopach (>= 2.42.0), BiocStyle, knitr (>= 1.22), rmarkdown (>= 1.12), testthat (>= 3.0.2), covr, vdiffr (>= 0.3.0)
# SystemRequirements: Python (>= 3.5), scikit-learn (>= 0.21.2), packaging
requirements:
  host:
    - 'bioconductor-biocparallel >=1.34.0,<1.35.0'
    - 'bioconductor-biostrings >=2.68.0,<2.69.0'
    - r-base
    - r-cli
    - r-cluster
    - 'r-cvtools >=0.3.2'
    - r-fpc
    - 'r-ggplot2 >=3.1.1'
    - 'r-ggseqlogo >=0.1'
    - r-mass
    - r-matrix
    - r-matrixstats
    - r-prettyunits
    - 'r-reshape2 >=1.4.3'
    - 'r-reticulate >=1.22'
  run:
    - 'bioconductor-biocparallel >=1.34.0,<1.35.0'
    - 'bioconductor-biostrings >=2.68.0,<2.69.0'
    - r-base
    - r-cli
    - r-cluster
    - 'r-cvtools >=0.3.2'
    - r-fpc
    - 'r-ggplot2 >=3.1.1'
    - 'r-ggseqlogo >=0.1'
    - r-mass
    - r-matrix
    - r-matrixstats
    - r-prettyunits
    - 'r-reshape2 >=1.4.3'
    - 'r-reticulate >=1.22'
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: 'GPL-3 | file LICENSE'
  summary: 'Identify Different Architectures of Sequence Elements'
  description: 'seqArchR enables unsupervised discovery of _de novo_ clusters with characteristic sequence architectures characterized by position-specific motifs or composition of stretches of nucleotides, e.g., CG-richness. seqArchR does _not_ require any specifications w.r.t. the number of clusters, the length of any individual motifs, or the distance between motifs if and when they occur in pairs/groups; it directly detects them from the data. seqArchR uses non-negative matrix factorization (NMF) as its backbone, and employs a chunking-based iterative procedure that enables processing of large sequence collections efficiently. Wrapper functions are provided for visualizing cluster architectures as sequence logos.'
  license_file: LICENSE

