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Matthew Stephens

Affiliations: 
Human Genetics University of Chicago, Chicago, IL 
 University of Washington, Seattle, Seattle, WA 
Area:
genetics, statistics
Website:
http://stephenslab.uchicago.edu/index.html
Google:
"Matthew Stephens"
Cross-listing: Neurotree

Parents

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Brian David Ripley grad student Oxford (MathTree)
Peter Donnelly post-doc Oxford (MathTree)

Children

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Michael Turchin grad student 2012- Chicago (Neurotree)
Sarah Urbit grad student 2013- Chicago (Neurotree)
Garrett Hellenthal grad student 2006 University of Washington (Neurotree)
Paul A. Scheet grad student 2006 University of Washington (Neurotree)
Xiaoquan Wen grad student 2011 Chicago (Neurotree)
Desislava Ivova Petkova grad student 2013 Chicago (Neurotree)
Barbara Elizabeth Engelhardt post-doc Chicago (Neurotree)
Jean Morrison post-doc Chicago (MathTree)
Gao Wang post-doc Chicago (Neurotree)
Matthew Barber post-doc 2006-2010 Chicago (Neurotree)
Yongtao Guan post-doc 2006-2010 Chicago (Neurotree)
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Publications

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Zhao S, Crouse W, Qian S, et al. (2024) Adjusting for genetic confounders in transcriptome-wide association studies improves discovery of risk genes of complex traits. Nature Genetics
Zou Y, Carbonetto P, Xie D, et al. (2023) Fast and flexible joint fine-mapping of multiple traits via the Sum of Single Effects model. Biorxiv : the Preprint Server For Biology
Morgante F, Carbonetto P, Wang G, et al. (2023) A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes. Plos Genetics. 19: e1010539
Zou Y, Carbonetto P, Wang G, et al. (2022) Fine-mapping from summary data with the "Sum of Single Effects" model. Plos Genetics. 18: e1010299
Barbeira AN, Bonazzola R, Gamazon ER, et al. (2021) Exploiting the GTEx resources to decipher the mechanisms at GWAS loci. Genome Biology. 22: 49
Gerard D, Stephens M. (2021) Unifying and Generalizing Methods for Removing Unwanted Variation Based on Negative Controls Statistica Sinica
Wang G, Sarkar A, Carbonetto P, et al. (2020) A simple new approach to variable selection in regression, with application to genetic fine mapping. Journal of the Royal Statistical Society. Series B, Statistical Methodology. 82: 1273-1300
Kim-Hellmuth S, Aguet F, Oliva M, et al. (2020) Cell type-specific genetic regulation of gene expression across human tissues. Science (New York, N.Y.). 369
Oliva M, Muñoz-Aguirre M, Kim-Hellmuth S, et al. (2020) The impact of sex on gene expression across human tissues. Science (New York, N.Y.). 369
Zhang Z, Luo K, Zou Z, et al. (2020) Genetic analyses support the contribution of mRNA N-methyladenosine (mA) modification to human disease heritability. Nature Genetics
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