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Wei-Qi Wei
Researcher at Vanderbilt University Medical Center
Publications - 108
Citations - 4793
Wei-Qi Wei is an academic researcher from Vanderbilt University Medical Center. The author has contributed to research in topics: Genome-wide association study & Odds ratio. The author has an hindex of 29, co-authored 106 publications receiving 2883 citations. Previous affiliations of Wei-Qi Wei include University of Minnesota & Mayo Clinic.
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Journal ArticleDOI
Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies
Wei Zhou,Jonas B. Nielsen,Lars G. Fritsche,Rounak Dey,Maiken Elvestad Gabrielsen,Brooke N. Wolford,Jonathon LeFaive,Peter VandeHaar,Sarah A. Gagliano,Aliya Gifford,Lisa Bastarache,Wei-Qi Wei,Joshua C. Denny,Joshua C. Denny,Maoxuan Lin,Kristian Hveem,Hyun Min Kang,Gonçalo R. Abecasis,Cristen J. Willer,Seunggeun Lee +19 more
TL;DR: SAIGE is a scalable and accurate generalized mixed model association test that can efficiently analyze large data sets while controlling for unbalanced case-control ratios and sample relatedness, as shown by applying SAIGE to the UK Biobank data for > 1,400 binary phenotypes.
Journal ArticleDOI
Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation
Patrick Wu,Aliya Gifford,Xiangrui Meng,Xue Li,Harry Campbell,Tim Varley,Juan Zhao,Robert J. Carroll,Lisa Bastarache,Joshua C. Denny,Evropi Theodoratou,Wei-Qi Wei +11 more
TL;DR: This study introduces the beta versions of I CD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD/ICD/PheWAS data for PhewAS in the EHR by investigating phenotype reproducibility and conducting a PheW AS.
Journal ArticleDOI
Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study
Abel N. Kho,M. Geoffrey Hayes,Laura J. Rasmussen-Torvik,Jennifer A. Pacheco,William K. Thompson,Loren L. Armstrong,Joshua C. Denny,Peggy L. Peissig,Aaron W. Miller,Wei-Qi Wei,Suzette J. Bielinski,Christopher G. Chute,Cynthia L. Leibson,Gail P. Jarvik,David R. Crosslin,Christopher S. Carlson,Katherine M. Newton,Wendy A. Wolf,Rex L. Chisholm,William L. Lowe +19 more
TL;DR: An algorithm using commonly available data from five different EMR data collected through routine clinical care can accurately identify type 2 diabetes cases and controls for genetic study across multiple institutions.
Journal ArticleDOI
Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record
Wei-Qi Wei,Lisa Bastarache,Robert J. Carroll,Joy E. Marlo,Travis J. Osterman,Eric R. Gamazon,Nancy J. Cox,Dan M. Roden,Joshua C. Denny +8 more
TL;DR: Three groupings of Electronic Health Record billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies.
Journal ArticleDOI
Extracting research-quality phenotypes from electronic health records to support precision medicine.
Wei-Qi Wei,Joshua C. Denny +1 more
TL;DR: The advantages and challenges of repurposing EHR data for genetic research are summarized and recent notable studies and novel approaches are highlighted to provide an overview of advanced EHR-based phenotyping.