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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "iPath" in publications use:'
type: software
license: GPL-2.0-only
title: 'iPath: iPath pipeline for detecting perturbed pathways at individual level'
version: 1.11.0
abstract: iPath is the Bioconductor package used for calculating personalized pathway
  score and test the association with survival outcomes. Abundant single-gene biomarkers
  have been identified and used in the clinics. However, hundreds of oncogenes or
  tumor-suppressor genes are involved during the process of tumorigenesis. We believe
  individual-level expression patterns of pre-defined pathways or gene sets are better
  biomarkers than single genes. In this study, we devised a computational method named
  iPath to identify prognostic biomarker pathways, one sample at a time. To test its
  utility, we conducted a pan-cancer analysis across 14 cancer types from The Cancer
  Genome Atlas and demonstrated that iPath is capable of identifying highly predictive
  biomarkers for clinical outcomes, including overall survival, tumor subtypes, and
  tumor stage classifications. We found that pathway-based biomarkers are more robust
  and effective than single genes.
authors:
- family-names: Su
  given-names: Kenong
  email: kenong.su@emory.edu
- family-names: Qin
  given-names: Zhaohui
  email: zhaohui.qin@emory.edu
preferred-citation:
  type: article
  title: Pan-Cancer Analysis of Pathway-Based Gene Expression Pattern at the Individual
    Level Reveals Novel Biomarkers of Clinical Prognosis
  authors:
  - family-names: Su
    given-names: Kenong
    email: kenong.su@emory.edu
  - family-names: Qin
    given-names: Steve
  year: '2021'
  journal: Cell Reports Methods
repository: https://bioc.r-universe.dev
repository-code: https://github.com/suke18/iPath
url: https://github.com/suke18/iPath
contact:
- family-names: Su
  given-names: Kenong
  email: kenong.su@emory.edu