Enhancing the Power of Genetic Association Studies through the Use of Silver Standard Cases Derived from Electronic Medical Records

Andrew McDavid, Paul K. Crane, Katherine M. Newton, David R. Crosslin, Wayne McCormick, Noah Weston, Kelly Ehrlich, Eugene Hart, Robert Harrison, Walter A. Kukull, Carla Rottscheit, Peggy Peissig, Elisha Stefanski, Catherine A. McCarty, Rebecca Lynn Zuvich, Marylyn D. Ritchie, Jonathan L. Haines, Joshua C. Denny, Gerard D. Schellenberg, Mariza de AndradeIftikhar Kullo, Rongling Li, Daniel Mirel, Andrew Crenshaw, James D. Bowen, Ge Li, Debby Tsuang, Susan McCurry, Linda Teri, Eric B. Larson, Gail P. Jarvik, Chris S. Carlson

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The feasibility of using imperfectly phenotyped "silver standard" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped with a gold standard technique. An analytic expression is derived for the power of a chi-square test of independence using either research-quality case/control samples alone, or augmented with silver standard data. The subset of the parameter space where inclusion of silver standard samples increases statistical power is identified. A case study of dementia subjects identified from electronic medical records from the Electronic Medical Records and Genomics (eMERGE) network, combined with subjects from two studies specifically targeting dementia, verifies these results.

Original languageEnglish (US)
Article numbere63481
JournalPloS one
Volume8
Issue number6
DOIs
StatePublished - Jun 10 2013

All Science Journal Classification (ASJC) codes

  • General

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