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Buhm Han

Showing results (41-50 of 96) with videos related to

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Bioinformatics (Oxford, England)|June 17, 2016
Using genomic annotations increases statistical power to detect eGenesDat Duong, Jennifer Zou, Farhad Hormozdiari, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Applying meta-analysis to genotype-tissue expression data from multiple tissues to identify eQTLs and increase the number of eGenesDat Duong, Lisa Gai, Sagi Snir, et al.
Human Molecular Genetics|February 25, 2016
A general framework for meta-analyzing dependent studies with overlapping subjects in association mappingBuhm Han, Dat Duong, Jae Hoon Sul, et al.
Nature Communications|February 25, 2021
Accurate imputation of human leukocyte antigens with CookHLASeungho Cook, Wanson Choi, Hyunjoon Lim, et al.
Nature Genetics|December 25, 2012
Chromatin marks identify critical cell types for fine mapping complex trait variantsGosia Trynka, Cynthia Sandor, Buhm Han, et al.
American Journal of Human Genetics|June 14, 2016
Imputing Phenotypes for Genome-wide Association StudiesFarhad Hormozdiari, Eun Yong Kang, Michael Bilow, et al.
Nature Communications|December 24, 2014
The HLA-DRβ1 amino acid positions 11-13-26 explain the majority of SLE-MHC associationsKwangwoo Kim, So-Young Bang, Hye-Soon Lee, et al.
Genetics|May 3, 2013
Rare variant association testing under low-coverage sequencingOron Navon, Jae Hoon Sul, Buhm Han, et al.
Plos Genetics|January 14, 2014
Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 miceEun Yong Kang, Buhm Han, Nicholas Furlotte, et al.
American Journal of Human Genetics|July 4, 2015
Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait LociGosia Trynka, Harm-Jan Westra, Kamil Slowikowski, et al.
Pageof 10

Showing results (41-50 of 96) with videos related to

Sort By:
Pageof 10
Bioinformatics (Oxford, England)|June 17, 2016
Using genomic annotations increases statistical power to detect eGenesDat Duong, Jennifer Zou, Farhad Hormozdiari, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Applying meta-analysis to genotype-tissue expression data from multiple tissues to identify eQTLs and increase the number of eGenesDat Duong, Lisa Gai, Sagi Snir, et al.
Human Molecular Genetics|February 25, 2016
A general framework for meta-analyzing dependent studies with overlapping subjects in association mappingBuhm Han, Dat Duong, Jae Hoon Sul, et al.
Nature Communications|February 25, 2021
Accurate imputation of human leukocyte antigens with CookHLASeungho Cook, Wanson Choi, Hyunjoon Lim, et al.
Nature Genetics|December 25, 2012
Chromatin marks identify critical cell types for fine mapping complex trait variantsGosia Trynka, Cynthia Sandor, Buhm Han, et al.
American Journal of Human Genetics|June 14, 2016
Imputing Phenotypes for Genome-wide Association StudiesFarhad Hormozdiari, Eun Yong Kang, Michael Bilow, et al.
Nature Communications|December 24, 2014
The HLA-DRβ1 amino acid positions 11-13-26 explain the majority of SLE-MHC associationsKwangwoo Kim, So-Young Bang, Hye-Soon Lee, et al.
Genetics|May 3, 2013
Rare variant association testing under low-coverage sequencingOron Navon, Jae Hoon Sul, Buhm Han, et al.
Plos Genetics|January 14, 2014
Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 miceEun Yong Kang, Buhm Han, Nicholas Furlotte, et al.
American Journal of Human Genetics|July 4, 2015
Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait LociGosia Trynka, Harm-Jan Westra, Kamil Slowikowski, et al.
Pageof 10