Back

Measuring genetic variation in the multi-ethnic Million Veteran Program (MVP)

Hunter-Zinck, H.; Shi,, Y.; Li, M.; Gorman, B. R.; Ji, S.-G.; Sun, N.; Webster, T.; Liem, A.; Hsieh, P.; Devineni, P.; Karnam, P.; Radhakrishnan, L.; Schmidt, J.; Assimes, T. L.; Huang, J.; Pan, C.; Humphries, D.; Brophy, M.; Moser, J.; Muralidhar, S.; Huang, G. D.; Przygodzki, R.; Concato, J.; Gaziano, J. M.; Gelernter, J.; ODonnell, C. J.; Hauser, E. R.; Zhao, H.-y.; OLeary, T. J.; Tsao, P. S.; Pyarajan, S.

2020-01-07 genetics
10.1101/2020.01.06.896613 bioRxiv
Show abstract

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect consented biosamples from at least one million Veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide genome-wide scan of the entire cohort, in parallel with whole genome sequencing, methylation, and other omics assays. Here, we present the design and performance of MVP 1.0 custom Axiom(R) array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality control analysis was developed and conducted on an initial tranche of 485,856 individuals leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high quality genotypes not only on common variants but also on rare variants. We confirmed the substantial ancestral diversity of MVP with nearly 30% non-European individuals, surpassing other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current data set has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.