# This file created by conda-build 3.21.8
# meta.yaml template originally from:
# /Users/runner/work/bioconda-recipes/bioconda-recipes/recipes/bioconductor-ppcseq, last modified Thu Nov  3 06:07:21 2022
# ------------------------------------------------

package:
  name: bioconductor-ppcseq
  version: 1.6.0
source:
  md5: 26ba8f7f77732973d7cdcd1229cf2b97
  url:
    - https://bioarchive.galaxyproject.org/ppcseq_1.6.0.tar.gz
    - https://bioconductor.org/packages/3.16/bioc/src/contrib/ppcseq_1.6.0.tar.gz
    - https://depot.galaxyproject.org/software/bioconductor-ppcseq/bioconductor-ppcseq_1.6.0_src_all.tar.gz
build:
  number: '0'
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  string: r42hb890f52_0
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  run:
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test:
  commands:
    - $R -e "library('ppcseq')"
about:
  description: Relative transcript abundance has proven to be a valuable tool for
    understanding the function of genes in biological systems. For the differential
    analysis of transcript abundance using RNA sequencing data, the negative binomial
    model is by far the most frequently adopted. However, common methods that are
    based on a negative binomial model are not robust to extreme outliers, which we
    found to be abundant in public datasets. So far, no rigorous and probabilistic
    methods for detection of outliers have been developed for RNA sequencing data,
    leaving the identification mostly to visual inspection. Recent advances in Bayesian
    computation allow large-scale comparison of observed data against its theoretical
    distribution given in a statistical model. Here we propose ppcseq, a key quality-control
    tool for identifying transcripts that include outlier data points in differential
    expression analysis, which do not follow a negative binomial distribution. Applying
    ppcseq to analyse several publicly available datasets using popular tools, we
    show that from 3 to 10 percent of differentially abundant transcripts across algorithms
    and datasets had statistics inflated by the presence of outliers.
  home: https://bioconductor.org/packages/3.16/bioc/html/ppcseq.html
  license: GPL-3
  license_file: /Users/runner/miniconda/conda-bld/bioconductor-ppcseq_1667471859440/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_/lib/R/share/licenses/GPL-3
  summary: Probabilistic Outlier Identification for RNA Sequencing Generalized Linear
    Models
extra:
  copy_test_source_files: true
  final: true
