Feasibility of Using Clinical Element Models (CEM) to Standardize Phenotype Variables in the Database of Genotypes and Phenotypes (dbGaP)

Ko Wei Lin, Melissa Tharp, Mike Conway, Alexander Hsieh, Mindy Ross, Jihoon Kim, Hyeon Eui Kim

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The database of Genotypes and Phenotypes (dbGaP) contains various types of data generated from genome-wide association studies (GWAS). These data can be used to facilitate novel scientific discoveries and to reduce cost and time for exploratory research. However, idiosyncrasies and inconsistencies in phenotype variable names are a major barrier to reusing these data. We addressed these challenges in standardizing phenotype variables by formalizing their descriptions using Clinical Element Models (CEM). Designed to represent clinical data, CEMs were highly expressive and thus were able to represent a majority (77.5%) of the 215 phenotype variable descriptions. However, their high expressivity also made it difficult to directly apply them to research data such as phenotype variables in dbGaP. Our study suggested that simplification of the template models makes it more straightforward to formally represent the key semantics of phenotype variables.

Original languageEnglish
Article numbere76384
JournalPLoS ONE
Volume8
Issue number9
DOIs
StatePublished - Sep 18 2013
Externally publishedYes

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