PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger-Reference-Cited by-同舟云学术

PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger

Published:2018-04 Issue:4 Volume:102 Page:592-608
ISSN:0002-9297
Container-title:The American Journal of Human Genetics
language:en
Short-container-title:The American Journal of Human Genetics

Author:

Verma Anurag,Lucas Anastasia,Verma Shefali S.,Zhang Yu,Josyula Navya,Khan Anqa,Hartzel Dustin N.,Lavage Daniel R.,Leader Joseph,Ritchie Marylyn D.,Pendergrass Sarah A.

Funder

Pennsylvania Department of Health

Publisher

Elsevier BV

Subject

Genetics (clinical),Genetics

Reference76 articles.

1. Detection of pleiotropy through a phenome-wide association study (PheWAS) of epidemiologic data as part of the Environmental Architecture for Genes Linked to Environment (EAGLE) study;Hall;PLoS Genet.,2014

2. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations;Denny;Bioinformatics,2010

3. Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network;Pendergrass;PLoS Genet.,2013

4. Phenome-wide association study to explore relationships between immune system related genetic loci and complex traits and diseases;Verma;PLoS ONE,2016

5. Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to eosinophilic esophagitis;Namjou;Front. Genet.,2014

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