Author

Sarah A. Pendergrass

Geisinger Health SystemORCID 0000-0002-0565-6522Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genetics· 2 Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Research Focus:GWAS / association mapping· 4 Organism:human· 4 Assay:electronic health records· 3 Assay:GWAS summary statistics· 3 Research Focus:benchmarking· 2 Research Focus:database / resource· 1 Research Focus:imputation· 1

Frequent Co-Authors

Navya Shilpa JosyulaiD· 3 shared Christopher R. BaueriD· 2 shared David R. CrossliniD· 2 shared Digna R. Velez EdwardsiD· 2 shared Felix R. DayiD· 2 shared Gail Pairitz JarvikiD· 2 shared Hakon H. HakonarsoniD· 2 shared Ian B. StanawayiD· 2 shared

Activity by Year

2018-2020 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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3 shared papersGenetics

Navya Shilpa JosyulaORCID

Mutual co-authors in cluster

Author profile →

6 papers

Recent·Most cited

Characterization of Genetic and Phenotypic Heterogeneity of Obstructive Sleep Apnea Using Electronic Health Records

Olivia J. Veatch, Christopher R. Bauer, Navya Shilpa Josyula, Diego R. Mazzotti, Brendan T Keenan, Kanika Bagai, Beth Ann Malow, Janet D. Robishaw, Allan I Pack, Sarah A. Pendergrass

The paper identifies genetic variants associated with obstructive sleep apnea using electronic health records and links them to comorbidities.

BMC Medical Genomics · Jul 25, 2020Peer-reviewedGenetics

A genome-wide association study of polycystic ovary syndrome identified from electronic health records

Yanfei Zhang, Kevin Ho, Jacob M. Keaton, Dustin N. Hartzel, Felix R. Day, Anne E. Justice, Navya Shilpa Josyula, Sarah A. Pendergrass, Ky’Era V. Actkins, Lea Karatheodoris Davis, Digna R. Velez Edwards, Brody Holohan, Andrea H. Ramirez, Ian B. Stanaway, David R. Crosslin, , Ming Ta Michael Lee

This paper identifies novel genetic variants associated with PCOS using EHR-based GWAS and validates them in independent cohorts.

American Journal of Obstetrics and Gynecology · Apr 11, 2020Peer-reviewedGenetic & Genomic Medicine

A large cross-ancestry meta-analysis of genome-wide association studies identifies 69 novel risk loci for primary open-angle glaucoma and includes a genetic link with Alzheimer's disease

Puya Gharahkhani, Eric Jorgenson, Pirro G. Hysi, Anthony P. Khawaja, Sarah A. Pendergrass, Xikun Han, Jue‐Sheng Ong, Alex William Hewitt, Ayellet V. Segrè, Robert P. Igo, Hélène Choquet, Ayub Qassim, Navya Shilpa Josyula, Jessica N. Cooke Bailey, Pieter W. M. Bonnemaijer, , Janey L. Wiggs

bioRxiv · Jan 30, 2020 · PreprintGenetics

A polygenic and phenotypic risk prediction for Polycystic Ovary Syndrome evaluated by Phenome-wide association studies

Yoonjung Yoonie Joo, Ky’Era V. Actkins, Jennifer A. Pacheco, Anna Okula Basile, Robert J. Carroll, David R. Crosslin, Felix R. Day, Joshua C. Denny, Digna R. Velez Edwards, Hakon H. Hakonarson, John B. Harley, Scott Joseph Hebbring, Kevin Ho, Gail Pairitz Jarvik, Michelle R. Jones, , Corrine Kolka Welt

This study develops a polygenic and phenotypic risk score for PCOS using EHR data, showing improved detection and identifying shared metabolic and endocrine comorbidities.

The Journal of Clinical Endocrinology & Metabolism · Jan 9, 2020Peer-reviewedBioinformatics

A simulation study investigating power estimates in Phenome-Wide Association Studies

Anurag Verma, Yuki Bradford, SCOTT M. DUDEK, Anastasia Lucas, Shefali S. Verma, Sarah A. Pendergrass, Marylyn DeRiggi Ritchie

This study simulates PheWAS to assess how sample size, case-control ratio, minor allele frequency, and disease penetrance affect statistical power for binary and quantitative traits.

BMC Bioinformatics · Apr 4, 2018Peer-reviewedGenomics

Characterizing and Managing Missing Structured Data in Electronic Health Records

Brett K. Beaulieu‐Jones, Daniel R. Lavage, John W Snyder, Jason H. Moore, Sarah A. Pendergrass, Christopher R. Bauer

The paper evaluates imputation methods for missing structured data in EHRs using clinical lab measures from 602,366 patients, showing some methods perform well while others are unsuitable for multiple imputation.

JMIR Medical Informatics · Feb 23, 2018Peer-reviewedBioinformatics