Expression quantitative trait loci information improves predictive modeling of disease relevance of non-coding genetic variation

Authors

Damien C. Croteau-Cronka, Harvard University
Angela J. Rogers, Harvard University
Towfique Raj, Harvard University
Michael J. McGeachie, Harvard University
Weiliang Qui, Harvard University
John P. Ziniti, Harvard University
Benjamin J. Stubbs, Harvard University
Liming Liang, Harvard University
Fernando D. Martinez, University of Arizona
Robert C. Strunk, Washington University School of Medicine in St. Louis
Robert F. Lemanske Jr., University of Wisconsin-Madison
Andrew H. Liu, University of Colorado, Denver
Barbara E. Stranger, Harvard University
Vincent J. Carey, Harvard University
Benjamin A. Raby, Harvard University

Journal

PLoS One

Publication Date

2015

Volume

10

Issue

10

Inclusive Pages

e0140758

Document Type

Open Access Publication

DOI

10.1371/journal.pone.0140758

Rights and Permissions

Croteau-Chonka DC, Rogers AJ, Raj T, McGeachie MJ, Qiu W, et al. (2015) Expression quantitative trait loci information improves predictive modeling of disease relevance of non-coding genetic variation. PLoS ONE 10(10): e0140758. doi: 10.1371/journal.pone.0140758

Recommended Citation

Croteau-Cronka, Damien C.; Rogers, Angela J.; Raj, Towfique; McGeachie, Michael J.; Qui, Weiliang; Ziniti, John P.; Stubbs, Benjamin J.; Liang, Liming; Martinez, Fernando D.; Strunk, Robert C.; Lemanske, Robert F. Jr.; Liu, Andrew H.; Stranger, Barbara E.; Carey, Vincent J.; and Raby, Benjamin A., "Expression quantitative trait loci information improves predictive modeling of disease relevance of non-coding genetic variation." PLoS One. 10, 10. e0140758. (2015).
https://digitalcommons.wustl.edu/open_access_pubs/5174