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10.1093/bioinformatics/btv076

http://scihub22266oqcxt.onion/10.1093/bioinformatics/btv076
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C4481696!4481696!25657332
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suck abstract from ncbi


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pmid25657332      Bioinformatics 2015 ; 31 (12): 1981-7
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  • Application of clinical text data for phenome-wide association studies (PheWASs) #MMPMID25657332
  • Hebbring SJ; Rastegar-Mojarad M; Ye Z; Mayer J; Jacobson C; Lin S
  • Bioinformatics 2015[Jun]; 31 (12): 1981-7 PMID25657332show ga
  • Motivation: Genome-wide association studies (GWASs) are effective for describing genetic complexities of common diseases. Phenome-wide association studies (PheWASs) offer an alternative and complementary approach to GWAS using data embedded in the electronic health record (EHR) to define the phenome. International Classification of Disease version 9 (ICD9) codes are used frequently to define the phenome, but using ICD9 codes alone misses other clinically relevant information from the EHR that can be used for PheWAS analyses and discovery.Results: As an alternative to ICD9 coding, a text-based phenome was defined by 23?384 clinically relevant terms extracted from Marshfield Clinic?s EHR. Five single nucleotide polymorphisms (SNPs) with known phenotypic associations were genotyped in 4235 individuals and associated across the text-based phenome. All five SNPs genotyped were associated with expected terms (P?
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