Temporal genetic association and temporal genetic causality methods for dissecting complex networks

Luan Lin; Quan Chen; Jeanne P. Hirsch; Seungyeul Yoo; Kayee Yeung; Roger E. Bumgarner; Zhidong Tu; Eric E. Schadt; Jun Zhu

doi:10.1038/s41467-018-06203-3

Nature Communications (Sep 2018)

Temporal genetic association and temporal genetic causality methods for dissecting complex networks

Luan Lin,
Quan Chen,
Jeanne P. Hirsch,
Seungyeul Yoo,
Kayee Yeung,
Roger E. Bumgarner,
Zhidong Tu,
Eric E. Schadt,
Jun Zhu

Affiliations

Luan Lin: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
Quan Chen: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
Jeanne P. Hirsch: Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai
Seungyeul Yoo: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
Kayee Yeung: Department of Microbiology, University of Washington
Roger E. Bumgarner: Department of Microbiology, University of Washington
Zhidong Tu: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
Eric E. Schadt: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
Jun Zhu: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai

DOI: https://doi.org/10.1038/s41467-018-06203-3
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 15

Abstract

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Temporal omics data have the potential to dissect complex biological networks. Here the authors develop methods for detecting temporal genetic loci (teQTLs) of quantitative traits monitored over time and inferring causal relationships between traits linked to the locus.

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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