ATLAS: an automated association test using probabilistically linked health records with application to genetic studies.

ABSTRACT:

Objective

Large amounts of health data are becoming available for biomedical research. Synthesizing information across databases may capture more comprehensive pictures of patient health and enable novel research studies. When no gold standard mappings between patient records are available, researchers may probabilistically link records from separate databases and analyze the linked data. However, previous linked data inference methods are constrained to certain linkage settings and exhibit low power. Here, we present ATLAS, an automated, flexible, and robust association testing algorithm for probabilistically linked data.

Materials and methods

Missing variables are imputed at various thresholds using a weighted average method that propagates uncertainty from probabilistic l

SUBMITTER: Zhang HG 

PROVIDER: S-EPMC8633652 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature