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Translational Psychiatry
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August 1, 2020
Association between DNA methylation levels in brain tissue and late-life depression in community-based participants
Anke Hüls, Chloe Robins, Karen N Conneely, et al.
American Journal of Human Genetics
|
July 30, 2024
Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia
Tingyang Hu, Randy L Parrish, Qile Dai, et al.
Biological Psychiatry
|
April 11, 2021
Brain DNA Methylation Patterns in CLDN5 Associated With Cognitive Decline
Anke Hüls, Chloe Robins, Karen N Conneely, et al.
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 bias
Colin 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 Test
Ni Zhao, Jun Chen, Ian M Carroll, 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 sizes
H 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 sequencing
H Richard Johnston, Pankaj Chopra, Thomas S Wingo, et al.
Epigenetics
|
March 13, 2023
Pruning and thresholding approach for methylation risk scores in multi-ancestry populations
Junyu 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 Learning
Randy 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 learning
Randy L Parrish, Aron S Buchman, Shinya Tasaki, et al.
Page
of 14
Search research articles
Search
Showing results (71-80 of 140) with videos related to
Sort By:
Page
of 14
Translational Psychiatry
|
August 1, 2020
Association between DNA methylation levels in brain tissue and late-life depression in community-based participants
Anke Hüls, Chloe Robins, Karen N Conneely, et al.
American Journal of Human Genetics
|
July 30, 2024
Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia
Tingyang Hu, Randy L Parrish, Qile Dai, et al.
Biological Psychiatry
|
April 11, 2021
Brain DNA Methylation Patterns in CLDN5 Associated With Cognitive Decline
Anke Hüls, Chloe Robins, Karen N Conneely, et al.
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 bias
Colin 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 Test
Ni Zhao, Jun Chen, Ian M Carroll, 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 sizes
H 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 sequencing
H Richard Johnston, Pankaj Chopra, Thomas S Wingo, et al.
Epigenetics
|
March 13, 2023
Pruning and thresholding approach for methylation risk scores in multi-ancestry populations
Junyu 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 Learning
Randy 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 learning
Randy L Parrish, Aron S Buchman, Shinya Tasaki, et al.
Page
of 14