American Journal of EpidemiologyGeneticsPeer-reviewed journal article
A system for phenotype harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program
Adrienne M. StilpiD, Leslie S. EmeryiD, Jai BroomeiD, Erin ButhiD, Alyna KhaniD, Cecelia A. LaurieiD, Fei Fei WangiD, Quenna WongiD, Dongquan CheniD, Catherine M. D’Augustine, Nancy L. Heard‐CostaiD, Chancellor Hohensee, W. Craig JohnsoniD, Lucia JuareziD, Jingmin Liu, Karen M. Mutalik, Laura M. RaffieldiD, Kerri L. WigginsiD, Paul S. de VriesiD, Tanika N. KellyiD, Charles L KooperbergiD, Pradeep NatarajaniD, Gina Marie PelosoiD, Patricia A. PeyseriD, Alex P. ReineriD, , Cathy C. LaurieiD
Abstract
Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 TOPMed studies per phenotype. We discuss the challenges faced in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.
- organism: human
- assay: GWAS summary statistics
- research focus: benchmarking
- approach: statistical model
- Citations
- 56
- FWCI
- 6.21
- Field percentile
- top 2%
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