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Showing results (141-150 of 210) with videos related to

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American Journal of Human Genetics|August 21, 2024
Inflation of polygenic risk scores caused by sample overlap and relatedness: Examples of a major risk of biasColin A Ellis, Karen L Oliver, Rebekah V Harris, et al.
American Journal of Human Genetics|May 11, 2015
Testing in Microbiome-Profiling Studies with MiRKAT, the Microbiome Regression-Based Kernel Association TestNi Zhao, Jun Chen, Ian M Carroll, et al.
Human Reproduction (Oxford, England)|June 26, 2007
Examination of reproductive aging milestones among women who carry the FMR1 premutationE G Allen, A K Sullivan, M Marcus, et al.
Proceedings of the National Academy of Sciences of the United States of America|September 17, 2017
Reply to Plüss et al.: The strength of PEMapper/PECaller lies in unbiased calling using large sample sizesH Richard Johnston, Pankaj Chopra, Thomas S Wingo, et al.
Proceedings of the National Academy of Sciences of the United States of America|February 23, 2017
PEMapper and PECaller provide a simplified approach to whole-genome sequencingH Richard Johnston, Pankaj Chopra, Thomas S Wingo, et al.
Epigenetics|March 13, 2023
Pruning and thresholding approach for methylation risk scores in multi-ancestry populationsJunyu Chen, Evan Gatev, Todd Everson, et al.
Medrxiv : the Preprint Server for Health Sciences|July 10, 2023
SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine LearningRandy L Parrish, Aron S Buchman, Shinya Tasaki, et al.
Nature Communications|August 5, 2024
SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learningRandy L Parrish, Aron S Buchman, Shinya Tasaki, et al.
Scientific Reports|May 19, 2019
Powerful and Efficient Strategies for Genetic Association Testing of Symptom and Questionnaire Data in Psychiatric Genetic StudiesAaron M Holleman, K Alaine Broadaway, Richard Duncan, et al.
Nature Communications|March 7, 2023
OTTERS: a powerful TWAS framework leveraging summary-level reference dataQile Dai, Geyu Zhou, Hongyu Zhao, et al.
Pageof 21

Showing results (141-150 of 210) with videos related to

Sort By:
Pageof 21
American Journal of Human Genetics|August 21, 2024
Inflation of polygenic risk scores caused by sample overlap and relatedness: Examples of a major risk of biasColin A Ellis, Karen L Oliver, Rebekah V Harris, et al.
American Journal of Human Genetics|May 11, 2015
Testing in Microbiome-Profiling Studies with MiRKAT, the Microbiome Regression-Based Kernel Association TestNi Zhao, Jun Chen, Ian M Carroll, et al.
Human Reproduction (Oxford, England)|June 26, 2007
Examination of reproductive aging milestones among women who carry the FMR1 premutationE G Allen, A K Sullivan, M Marcus, et al.
Proceedings of the National Academy of Sciences of the United States of America|September 17, 2017
Reply to Plüss et al.: The strength of PEMapper/PECaller lies in unbiased calling using large sample sizesH Richard Johnston, Pankaj Chopra, Thomas S Wingo, et al.
Proceedings of the National Academy of Sciences of the United States of America|February 23, 2017
PEMapper and PECaller provide a simplified approach to whole-genome sequencingH Richard Johnston, Pankaj Chopra, Thomas S Wingo, et al.
Epigenetics|March 13, 2023
Pruning and thresholding approach for methylation risk scores in multi-ancestry populationsJunyu Chen, Evan Gatev, Todd Everson, et al.
Medrxiv : the Preprint Server for Health Sciences|July 10, 2023
SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine LearningRandy L Parrish, Aron S Buchman, Shinya Tasaki, et al.
Nature Communications|August 5, 2024
SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learningRandy L Parrish, Aron S Buchman, Shinya Tasaki, et al.
Scientific Reports|May 19, 2019
Powerful and Efficient Strategies for Genetic Association Testing of Symptom and Questionnaire Data in Psychiatric Genetic StudiesAaron M Holleman, K Alaine Broadaway, Richard Duncan, et al.
Nature Communications|March 7, 2023
OTTERS: a powerful TWAS framework leveraging summary-level reference dataQile Dai, Geyu Zhou, Hongyu Zhao, et al.
Pageof 21