PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies.

ABSTRACT:

Objective

Standard approaches for large scale phenotypic screens using electronic health record (EHR) data apply thresholds, such as ≥2 diagnosis codes, to define subjects as having a phenotype. However, the variation in the accuracy of diagnosis codes can impair the power of such screens. Our objective was to develop and evaluate an approach which converts diagnosis codes into a probability of a phenotype (PheProb). We hypothesized that this alternate approach for defining phenotypes would improve power for genetic association studies.

Methods

The PheProb approach employs unsupervised clustering to separate patients into 2 groups based on diagnosis codes. Subjects are assigned a probability of having the phenotype based on the number of diagnosis codes. This approach was de

SUBMITTER: Sinnott JA 

PROVIDER: S-EPMC6915826 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature