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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "rgsepd" in publications use:'
type: software
license: GPL-3.0-only
title: 'rgsepd: Gene Set Enrichment / Projection Displays'
version: 1.37.0
doi: 10.1186/s12859-019-2697-5
abstract: R/GSEPD is a bioinformatics package for R to help disambiguate transcriptome
  samples (a matrix of RNA-Seq counts at transcript IDs) by automating differential
  expression (with DESeq2), then gene set enrichment (with GOSeq), and finally a N-dimensional
  projection to quantify in which ways each sample is like either treatment group.
authors:
- family-names: Stamm
  given-names: Karl
  email: karl.stamm@gmail.com
preferred-citation:
  type: article
  title: 'GSEPD: a Bioconductor package for RNA-seq gene set enrichment and projection
    display'
  authors:
  - family-names: Stamm
    given-names: Karl
    email: karl.stamm@gmail.com
  - family-names: Tomita-Mitchell
    given-names: Aoy
  - family-names: Bozdag
    given-names: Serdar
    email: serdar.bozdag@marquette.edu
  year: '2019'
  notes: R package version 1.37.0
  doi: 10.1186/s12859-019-2697-5
  journal: BMC Bioinformatics
  publisher:
    name: Springer Nature
  volume: '20'
  issue: '1'
  issn: 1471-2105
  abstract: RNA-seq, wherein RNA transcripts expressed in a sample are sequenced and
    quantified, has become a widely used technique to study disease and development.
    With RNA-seq, transcription abundance can be measured, differential expression
    genes between groups and functional enrichment of those genes can be computed.
    However, biological insights from RNA-seq are often limited by computational analysis
    and the enormous volume of resulting data, preventing facile and meaningful review
    and interpretation of gene expression profiles. Particularly, in cases where the
    samples under study exhibit uncontrolled variation, deeper analysis of functional
    enrichment would be necessary to visualize samples' gene expression activity under
    each biological function.
  url: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2697-5
  start: '115'
repository: https://bioc.r-universe.dev
date-released: '2022-03-22'
contact:
- family-names: Stamm
  given-names: Karl
  email: karl.stamm@gmail.com