On the cross-population generalizability of gene expression prediction models

The genetic control of gene expression is a core component of human physiology. For the past several years, transcriptome-wide association studies have leveraged large datasets of linked genotype and RNA sequencing information to create a powerful gene-based test of association that has been used in...

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Bibliographic Details
Published in:	PLoS genetics Vol. 16; no. 8; p. e1008927
Main Authors:	Keys, Kevin L., Mak, Angel C. Y., White, Marquitta J., Eckalbar, Walter L., Dahl, Andrew W., Mefford, Joel, Mikhaylova, Anna V., Contreras, María G., Elhawary, Jennifer R., Eng, Celeste, Hu, Donglei, Huntsman, Scott, Oh, Sam S., Salazar, Sandra, Lenoir, Michael A., Ye, Jimmie C., Thornton, Timothy A., Zaitlen, Noah, Burchard, Esteban G., Gignoux, Christopher R.
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 14.08.2020 Public Library of Science (PLoS)
Subjects:	Asthma Bioengineering Biology and Life Sciences Black or African American - genetics Datasets Gene expression Gene Expression Profiling - methods Gene Expression Profiling - standards Genetic control Genome-Wide Association Study - methods Genome-Wide Association Study - standards Genomes Genotype & phenotype Genotypes Humans Methods Models, Genetic People and Places Physical Sciences Population Population genetics Precision medicine Prediction models Quantitative Trait Loci Reference Standards Research and Analysis Methods Ribonucleic acid RNA RNA sequencing RNA-Seq - methods RNA-Seq - standards Software Supervision Transcriptome United States San Francisco California California United States > US Colorado
ISSN:	1553-7404, 1553-7390, 1553-7404
Online Access:	Get full text
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