A haplotype reference panel constructed from 490,319 UK Biobank genomes improves genotype imputation for global populations
Wienbrandt, L.; Priess, C.; Schmöhl, M.; Neff, V.; Gretsova, M.; Torres, G.; Wacker, E. M.; Franke, A.; Ellinghaus, D.
Show abstract
We constructed a genotype imputation reference panel from whole-genome sequence data of 490,319 UK Biobank participants and enabled both standalone and cloud-based phasing and imputation through EagleImp and EagleImp-RAP within the UK Biobank Research Analysis Platform. The UK Biobank reference panel achieves lower phasing switch error rates than the widely used TOPMed r3 panel (133,597 individuals) for all global superpopulations except AMR and for 25 of 26 1000 Genomes Project subpopulations. Imputation accuracy, measured by mean absolute error, improved for four of five superpopulations and 12 subpopulations for variants with minor allele frequencies down to 0.01%. Estimated squared correlation further improved across all five superpopulations and 22 subpopulations, with the largest gains in East and South Asian populations. Re-imputation of COVID-19 GWAS datasets from Italy, Germany, Spain and Norway demonstrated that common-variant imputation remains unsaturated, enhancing the discovery of genome-wide significant loci and improving fine-mapping resolution.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Multi-trait GWAS for diverse ancestries: Mapping the knowledge gap 95%
- Efficient blockLASSO for Polygenic Scores with Applications to All of Us and UK Biobank 94%
- Systematic benchmark of state-of-the-art variant calling pipelines identifies major factors affecting accuracy of coding sequence variant discovery 94%
Similar papers in this journal
"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.