Pathway-level information extractor (PLIER) for gene expression data

Nat Methods. 2019 Jul;16(7):607-610. doi: 10.1038/s41592-019-0456-1. Epub 2019 Jun 27.

Abstract

A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER) ( https://github.com/wgmao/PLIER and http://gobie.csb.pitt.edu/PLIER ), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Gene Expression Regulation*
  • Humans
  • Information Storage and Retrieval*
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci