Pitfalls of Merging GWAS Data: Lessons Learned in the eMERGE Network and Quality Control Procedures to Maintain High Data Quality

Genome-wide association studies (GWAS) are a useful approach in the study of the genetic components of complex phenotypes. Aside from large cohorts, GWAS have generally been limited to the study of one or a few diseases or traits. The emergence of biobanks linked to electronic medical records (EMRs)...

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Detalhes bibliográficos
Main Authors: Zuvich, Rebecca L., Armstrong, Loren L., Bielinski, Suzette J., Bradford, Yuki, Carlson, Christopher S., Crawford, Dana C., Crenshaw, Andrew T., de Andrade, Mariza, Doheny, Kimberly F., Haines, Jonathan L., Hayes, M. Geoffrey, Jarvik, Gail P., Jiang, Lan, Kullo, Iftikhar J., Li, Rongling, Ling, Hua, Manolio, Teri A., Matsumoto, Martha E., McCarty, Catherine A., McDavid, Andrew N., Mirel, Daniel B., Olson, Lana M., Paschall, Justin E., Pugh, Elizabeth W., Rasmussen, Luke V., Rasmussen-Torvik, Laura J., Turner, Stephen D., Wilke, Russell A., Ritchie, Marylyn D.
Formato: Artigo
Idioma:Inglês
Publicado em: 2011
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3592376/
https://ncbi.nlm.nih.gov/pubmed/22125226
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/gepi.20639
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