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

Weiguang Mao, Elena Zaslavsky, Boris M. Hartmann, Stuart C. Sealfon, Maria Chikina

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


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) ( and, 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.

Original languageEnglish
Pages (from-to)607-610
Number of pages4
JournalNature Methods
Issue number7
StatePublished - 1 Jul 2019


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