Translating genome wide association study results to associations among common diseases: In silico study with an electronic medical record

Highlights • An in silico model on the basis of summary GWAS and SNP LD data was built to represent a disease map. • Clinical data from a large and long running EMR was used to validate this disease map. • SNP-to-disease linkage explains only a small fraction of associations among diseases in an EMR...

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Veröffentlicht in:International journal of medical informatics (Shannon, Ireland) Ireland), 2013-09, Vol.82 (9), p.864-874
Hauptverfasser: Anand, Vibha, Rosenman, Marc B, Downs, Stephen M
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container_title International journal of medical informatics (Shannon, Ireland)
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creator Anand, Vibha
Rosenman, Marc B
Downs, Stephen M
description Highlights • An in silico model on the basis of summary GWAS and SNP LD data was built to represent a disease map. • Clinical data from a large and long running EMR was used to validate this disease map. • SNP-to-disease linkage explains only a small fraction of associations among diseases in an EMR. • Thus far clinical data has much greater predictive power for all diseases measured.
doi_str_mv 10.1016/j.ijmedinf.2013.05.003
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source MEDLINE; ScienceDirect Journals (5 years ago - present)
subjects Algorithms
Bayesian network
Bioinformatics
Computational Biology
Computer Simulation
Data mining
Databases, Genetic
Disease - genetics
Electronic Health Records - utilization
Electronic medical records (EMRs)
Genetic Predisposition to Disease
Genome Wide Association Studies (GWAS)
Genome, Human
Genome-Wide Association Study
Humans
In silico
Integration
Internal Medicine
Other
Polymorphism, Single Nucleotide - genetics
Single nucleotide polymorphisms (SNPs)
title Translating genome wide association study results to associations among common diseases: In silico study with an electronic medical record
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