Pathway analysis by randomization incorporating structure - Paris: An update

Mariusz Butkiewicz, Jessica N. Cooke Bailey, Alex Frase, Scott Dudek, Brian L. Yaspan, Marylyn D. Ritchie, Sarah A. Pendergrass, Jonathan L. Haines

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Motivation: We present an update to the pathway enrichment analysis tool 'Pathway Analysis by Randomization Incorporating Structure (Paris)' that determines aggregated association signals generated from genome-wide association study results. Pathway-based analyses highlight biological pathways associated with phenotypes. Paris uses a unique permutation strategy to evaluate the genomic structure of interrogated pathways, through permutation testing of genomic features, thus eliminating many of the over-testing concerns arising with other pathway analysis approaches. Results: We have updated Paris to incorporate expanded pathway definitions through the incorporation of new expert knowledge from multiple database sources, through customized user provided pathways, and other improvements in user flexibility and functionality. Availability and implementation: Paris is freely available to all users at https://ritchielab.psu.edu/software/Paris-download.

Original languageEnglish (US)
Pages (from-to)2361-2363
Number of pages3
JournalBioinformatics
Volume32
Issue number15
DOIs
StatePublished - Aug 1 2016

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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