Mao, Weiguang; Zaslavsky, Elena; Hartmann, Boris M; Sealfon, Stuart C; Chikina, Maria
Nature methods,
07/2019, Volume:
16, Issue:
7
Journal Article
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.
PDF