Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis

Igor Mandric; Tommer Schwarz; Arunabha Majumdar; Kangcheng Hou; Leah Briscoe; Richard Perez; Meena Subramaniam; Christoph Hafemeister; Rahul Satija; Chun Jimmie Ye; Bogdan Pasaniuc; Eran Halperin

doi:10.1038/s41467-020-19365-w

Nature Communications (Oct 2020)

Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis

Igor Mandric,
Tommer Schwarz,
Arunabha Majumdar,
Kangcheng Hou,
Leah Briscoe,
Richard Perez,
Meena Subramaniam,
Christoph Hafemeister,
Rahul Satija,
Chun Jimmie Ye,
Bogdan Pasaniuc,
Eran Halperin

Affiliations

Igor Mandric: Department of Computer Science, University of California Los Angeles
Tommer Schwarz: Bioinformatics Interdepartmental Program, University of California Los Angeles
Arunabha Majumdar: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles
Kangcheng Hou: Bioinformatics Interdepartmental Program, University of California Los Angeles
Leah Briscoe: Bioinformatics Interdepartmental Program, University of California Los Angeles
Richard Perez: Institute for Human Genetics, University of California San Francisco
Meena Subramaniam: Institute for Human Genetics, University of California San Francisco
Christoph Hafemeister: New York Genome Center
Rahul Satija: New York Genome Center
Chun Jimmie Ye: Institute for Human Genetics, University of California San Francisco
Bogdan Pasaniuc: Bioinformatics Interdepartmental Program, University of California Los Angeles
Eran Halperin: Department of Computer Science, University of California Los Angeles

DOI: https://doi.org/10.1038/s41467-020-19365-w
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 9

Abstract

Read online

Single cell RNA-sequencing can be a powerful approach to characterizing cell composition in a population of cells but is thought to be too expensive for population-scale analyses. Here, the authors show how lower coverage of more samples can increase the power to detect cell-type-specific eQTL.

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/

About the journal