A Bayesian framework for multiple trait colocalization from summary association statistics

C Giambartolomei, J Zhenli Liu, W Zhang… - …, 2018 - academic.oup.com
Motivation Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …
被引用次数：234 相关文章

A Bayesian framework for multiple trait colocalization from summary association statistics

C Giambartolomei, JZ Liu, W Zhang… - …, 2018 - pure.johnshopkins.edu
Motivation: Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …

A Bayesian framework for multiple trait colocalization from summary association statistics

C Giambartolomei, JZ Liu, W Zhang, M Hauberg, H Shi… - Bioinformatics, 2018 - pure.au.dk
Motivation: Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …

A Bayesian framework for multiple trait colocalization from summary association statistics.

C Giambartolomei, JZ Liu, W Zhang… - …, 2018 - search.ebscohost.com
Motivation Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …

A Bayesian framework for multiple trait colocalization from summary association statistics

C Giambartolomei, JZ Liu, W Zhang… - Bioinformatics …, 2018 - pubmed.ncbi.nlm.nih.gov
Motivation Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …

A Bayesian framework for multiple trait colocalization from summary association statistics.

C Giambartolomei, J Zhenli Liu, W Zhang… - Bioinformatics (Oxford …, 2018 - escholarship.org
Motivation: Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …
[PDF] academia.edu

[PDF][PDF] A Bayesian Framework for Multiple Trait Colo-calization from Summary Association Statistics

C Giambartolomei, JZ Liu, W Zhang, M Hauberg - academia.edu
Motivation: Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …

A Bayesian framework for multiple trait colocalization from summary association statistics.

C Giambartolomei, W Zhang, M Hauberg… - Bioinformatics (Oxford …, 2018 - europepmc.org
Results We applied moloc to schizophrenia (SCZ) and eQTL/mQTL data derived from
human brain tissue and identified 52 candidate genes that influence SCZ through …
[PDF] archive.org

[PDF][PDF] A Bayesian Framework for Multiple Trait Colo-calization from Summary Association Statistics

C Giambartolomei, JZ Liu, W Zhang, M Hauberg - scholar.archive.org
Motivation: Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …

A Bayesian framework for multiple trait colocalization from summary association statistics

C Giambartolomei, J Zhenli Liu, W Zhang… - …, 2018 - academic.oup.com
Motivation Most genetic variants implicated in complex diseases by genome-wide
association studies (GWAS) are non-coding, making it challenging to understand the …