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Hae Kyung Im

Showing results (1-10 of 101) with videos related to

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Cell Genomics|May 15, 2025
Meet the author: Hae Kyung ImHae Kyung Im
Bioinformatics (Oxford, England)|November 6, 2018
ukbREST: efficient and streamlined data access for reproducible research in large biobanksMilton Pividori, Hae Kyung Im
American Journal of Human Genetics|January 21, 2026
A gene-specific variance-control approach corrects polygenicity-driven inflation observed in transcriptome-wide association studiesYanyu Liang, Festus Nyasimi, Hae Kyung Im
Biorxiv : the Preprint Server for Biology|October 31, 2023
Pervasive polygenicity of complex traits inflates false positive rates in transcriptome-wide association studiesYanyu Liang, Festus Nyasimi, Hae Kyung Im
Nature Communications|August 23, 2020
CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analysesXuan Zhou, Hae Kyung Im, S Hong Lee
Ecology|February 4, 2010
Accounting for animal movement in estimation of resource selection functions: sampling and data analysisJames D Forester, Hae Kyung Im, Paul J Rathouz
American Journal of Human Genetics|April 3, 2012
On sharing quantitative trait GWAS results in an era of multiple-omics data and the limits of genomic privacyHae Kyung Im, Eric R Gamazon, Dan L Nicolae, et al.
Nature Communications|March 4, 2021
A scalable unified framework of total and allele-specific counts for cis-QTL, fine-mapping, and predictionYanyu Liang, François Aguet, Alvaro N Barbeira, et al.
Genetic Epidemiology|November 5, 2013
Quantitative allelic test--a fast test for very large association studiesSang Mee Lee, Theodore G Karrison, Nancy J Cox, et al.
The Lancet. Respiratory Medicine|May 1, 2019
Shared and distinct genetic risk factors for childhood-onset and adult-onset asthma: genome-wide and transcriptome-wide studiesMilton Pividori, Nathan Schoettler, Dan L Nicolae, et al.
Pageof 11

Showing results (1-10 of 101) with videos related to

Sort By:
Pageof 11
Cell Genomics|May 15, 2025
Meet the author: Hae Kyung ImHae Kyung Im
Bioinformatics (Oxford, England)|November 6, 2018
ukbREST: efficient and streamlined data access for reproducible research in large biobanksMilton Pividori, Hae Kyung Im
American Journal of Human Genetics|January 21, 2026
A gene-specific variance-control approach corrects polygenicity-driven inflation observed in transcriptome-wide association studiesYanyu Liang, Festus Nyasimi, Hae Kyung Im
Biorxiv : the Preprint Server for Biology|October 31, 2023
Pervasive polygenicity of complex traits inflates false positive rates in transcriptome-wide association studiesYanyu Liang, Festus Nyasimi, Hae Kyung Im
Nature Communications|August 23, 2020
CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analysesXuan Zhou, Hae Kyung Im, S Hong Lee
Ecology|February 4, 2010
Accounting for animal movement in estimation of resource selection functions: sampling and data analysisJames D Forester, Hae Kyung Im, Paul J Rathouz
American Journal of Human Genetics|April 3, 2012
On sharing quantitative trait GWAS results in an era of multiple-omics data and the limits of genomic privacyHae Kyung Im, Eric R Gamazon, Dan L Nicolae, et al.
Nature Communications|March 4, 2021
A scalable unified framework of total and allele-specific counts for cis-QTL, fine-mapping, and predictionYanyu Liang, François Aguet, Alvaro N Barbeira, et al.
Genetic Epidemiology|November 5, 2013
Quantitative allelic test--a fast test for very large association studiesSang Mee Lee, Theodore G Karrison, Nancy J Cox, et al.
The Lancet. Respiratory Medicine|May 1, 2019
Shared and distinct genetic risk factors for childhood-onset and adult-onset asthma: genome-wide and transcriptome-wide studiesMilton Pividori, Nathan Schoettler, Dan L Nicolae, et al.
Pageof 11