# This file created by conda-build 3.21.4
# meta.yaml template originally from:
# /opt/recipe, last modified Wed Nov  3 08:06:58 2021
# ------------------------------------------------

package:
  name: bioconductor-scde
  version: 2.22.0
source:
  md5: 466449f23604948adaef7b4b67afd70d
  url:
    - https://bioarchive.galaxyproject.org/scde_2.22.0.tar.gz
    - https://bioconductor.org/packages/3.14/bioc/src/contrib/scde_2.22.0.tar.gz
    - https://depot.galaxyproject.org/software/bioconductor-scde/bioconductor-scde_2.22.0_src_all.tar.gz
build:
  number: '0'
  rpaths:
    - lib/
    - lib/R/lib/
  string: r41h399db7b_0
requirements:
  build:
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  run:
    - bioconductor-biocparallel >=1.28.0,<1.29.0
    - bioconductor-edger >=3.36.0,<3.37.0
    - bioconductor-pcamethods >=1.86.0,<1.87.0
    - libblas >=3.8.0,<4.0a0
    - libgcc-ng >=9.4.0
    - liblapack >=3.8.0,<4.0a0
    - libstdcxx-ng >=9.4.0
    - r-base >=4.1,<4.2.0a0
    - r-cairo
    - r-extremes
    - r-flexmix
    - r-mass
    - r-mgcv
    - r-nnet
    - r-quantreg
    - r-rcolorbrewer
    - r-rcpp >=0.10.4
    - r-rcpparmadillo >=0.5.400.2.0
    - r-rjson
    - r-rmtstat
    - r-rook
test:
  commands:
    - $R -e "library('scde')"
about:
  description: 'The scde package implements a set of statistical methods for analyzing
    single-cell RNA-seq data. scde fits individual error models for single-cell RNA-seq
    measurements. These models can then be used for assessment of differential expression
    between groups of cells, as well as other types of analysis. The scde package
    also contains the pagoda framework which applies pathway and gene set overdispersion
    analysis to identify and characterize putative cell subpopulations based on transcriptional
    signatures. The overall approach to the differential expression analysis is detailed
    in the following publication: "Bayesian approach to single-cell differential expression
    analysis" (Kharchenko PV, Silberstein L, Scadden DT, Nature Methods, doi: 10.1038/nmeth.2967).
    The overall approach to subpopulation identification and characterization is detailed
    in the following pre-print: "Characterizing transcriptional heterogeneity through
    pathway and gene set overdispersion analysis" (Fan J, Salathia N, Liu R, Kaeser
    G, Yung Y, Herman J, Kaper F, Fan JB, Zhang K, Chun J, and Kharchenko PV, Nature
    Methods, doi:10.1038/nmeth.3734).'
  home: https://bioconductor.org/packages/3.14/bioc/html/scde.html
  license: GPL-2
  license_file: /opt/conda/conda-bld/bioconductor-scde_1635933503318/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/R/share/licenses/GPL-2
  summary: Single Cell Differential Expression
extra:
  copy_test_source_files: true
  final: true
  identifiers:
    - biotools:scde
    - doi:10.1038/nmeth.2967
