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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 "Pigengene" in publications use:'
type: software
title: 'Pigengene: Infers biological signatures from gene expression data'
version: 1.31.2
identifiers:
- type: doi
  value: 10.32614/CRAN.package.Pigengene
abstract: Pigengene package provides an efficient way to infer biological signatures
  from gene expression profiles. The signatures are independent from the underlying
  platform, e.g., the input can be microarray or RNA Seq data. It can even infer the
  signatures using data from one platform, and evaluate them on the other. Pigengene
  identifies the modules (clusters) of highly coexpressed genes using coexpression
  network analysis, summarizes the biological information of each module in an eigengene,
  learns a Bayesian network that models the probabilistic dependencies between modules,
  and builds a decision tree based on the expression of eigengenes.
authors:
- family-names: Zare
  given-names: Habil
  email: zare@u.washington.edu
- family-names: Foroushani
  given-names: Amir
- family-names: Agrahari
  given-names: Rupesh
- family-names: Short
  given-names: Meghan
- family-names: Mehta
  given-names: Isha
- family-names: Emami
  given-names: Neda
- family-names: Sajedi
  given-names: Sogand
preferred-citation:
  type: article
  title: 'Large-scale gene network analysis reveals the significance of extracellular
    matrix pathway and homeobox genes in acute myeloid leukemia: an introduction to
    the Pigengene package and its applications'
  authors:
  - family-names: Foroushani
    given-names: Amir
  - family-names: al.
    given-names: et
  journal: BMC Medical Genomics
  year: '2017'
  volume: '10'
  issue: '1'
  month: '3'
  start: '16'
repository: https://bioc.r-universe.dev
commit: e04cac6c9f4b7c19ba4c47a4d3c4608b5e637a83
date-released: '2016-03-31'
contact:
- family-names: Zare
  given-names: Habil
  email: zare@u.washington.edu