RT Journal Article
SR Electronic
T1 Pathway enrichment analysis of -<em>omics</em> data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 232835
DO 10.1101/232835
A1 Jüri Reimand
A1 Ruth Isserlin
A1 Veronique Voisin
A1 Mike Kucera
A1 Christian Tannus-Lopes
A1 Asha Rostamianfar
A1 Lina Wadi
A1 Mona Meyer
A1 Jeff Wong
A1 Changjiang Xu
A1 Daniele Merico
A1 Gary D. Bader
YR 2017
UL http://biorxiv.org/content/early/2017/12/12/232835.abstract
AB Pathway enrichment analysis helps gain mechanistic insight into large gene lists typically resulting from genome scale (–omics) experiments. It identifies biological pathways that are enriched in the gene list more than expected by chance. We explain pathway enrichment analysis and present a practical step-by-step guide to help interpret gene lists resulting from RNA-seq and genome sequencing experiments. The protocol comprises three major steps: define a gene list from genome scale data, determine statistically enriched pathways, and visualize and interpret the results. We focus on differentially expressed genes and mutated cancer genes, however the described principles can be applied to diverse –omics data. The protocol is designed for biologists with no prior bioinformatics training and uses freely available software including g:Profiler, GSEA, Cytoscape and Enrichment Map.