A1 Refereed original research article in a scientific journal
PASI: A novel pathway method to identify delicate group effects
Authors: Maria K. Jaakkola, Aidan J. McGlinchey, Riku Klen, Laura L. Elo
Publisher: PUBLIC LIBRARY SCIENCE
Publication year: 2018
Journal: PLoS ONE
Journal name in source: PLOS ONE
Journal acronym: PLOS ONE
Article number: e0199991
Volume: 13
Issue: 7
Number of pages: 13
ISSN: 1932-6203
DOI: https://doi.org/10.1371/journal.pone.0199991
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/32156420
Abstract
Pathway analysis is a common approach in diverse biomedical studies, yet the currently-available pathway tools do not typically support the increasingly popular personalized analyses. Another weakness of the currently-available pathway methods is their inability to handle challenging data with only modest group-based effects compared to natural individual variation. In an effort to address these issues, this study presents a novel pathway method PASI (Pathway Analysis for Sample-level Information) and demonstrates its performance on complex diseases with different levels of group-based differences in gene expression. PASI is freely available as an R package.
Pathway analysis is a common approach in diverse biomedical studies, yet the currently-available pathway tools do not typically support the increasingly popular personalized analyses. Another weakness of the currently-available pathway methods is their inability to handle challenging data with only modest group-based effects compared to natural individual variation. In an effort to address these issues, this study presents a novel pathway method PASI (Pathway Analysis for Sample-level Information) and demonstrates its performance on complex diseases with different levels of group-based differences in gene expression. PASI is freely available as an R package.
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