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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Detaylı Bibliyografya
Asıl Yazarlar: 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.
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: 2011
Konular:
Article
Online Erişim: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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