Integrative differential expression and gene set enrichment analysis using summary statistics for scRNA-seq studies

Ying Ma; Shiquan Sun; Xuequn Shang; Evan T. Keller; Mengjie Chen; Xiang Zhou

doi:10.1038/s41467-020-15298-6

Nature Communications (Mar 2020)

Integrative differential expression and gene set enrichment analysis using summary statistics for scRNA-seq studies

Ying Ma,
Shiquan Sun,
Xuequn Shang,
Evan T. Keller,
Mengjie Chen,
Xiang Zhou

Affiliations

Ying Ma: Department of Biostatistics, University of Michigan
Shiquan Sun: Department of Biostatistics, University of Michigan
Xuequn Shang: School of Computer Science, Northwestern Polytechnical University
Evan T. Keller: Department of Urology, University of Michigan
Mengjie Chen: Department of Human Genetics, University of Chicago
Xiang Zhou: Department of Biostatistics, University of Michigan

DOI: https://doi.org/10.1038/s41467-020-15298-6
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 13

Abstract

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Differential expression (DE) and gene set enrichment (GSE) analysis tend to be carried out separately. Here, the authors present iDEA (integrative Differential expression and gene set Enrichment Analysis) for the analysis of scRNAseq data which uses a Baysian approach to jointly model DE and GSE for improved power in both tasks.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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