Fast and accurate long-range phasing in a UK Biobank cohort

By Po-Ru Loh, Pier Francesco Palamara, Alkes L Price. 2015

338 citations recorded by the source corpus.

Recent work has leveraged the extensive genotyping of the Icelandic population to perform long-range phasing (LRP), enabling accurate imputation and association analysis of rare variants in target samples typed on genotyping arrays. Here we develop a fast and accurate LRP method, Eagle, that extends this paradigm to populations with much smaller proportions of genotyped samples by harnessing long (>4-cM) identical-by-descent (IBD) tracts shared among distantly related individuals. We applied Eagle to N ≈ 150,000 samples (0.2% of the British population) from the UK Biobank, and we determined that it is 1–2 orders of magnitude faster than existing methods while achieving similar or better phasing accuracy (switch error rate ≈ 0.3%, corresponding to perfect phase in a majority of 10-Mb segments). We also observed that, when used within an imputation pipeline, Eagle prephasing improved downstream imputation accuracy in comparison to prephasing in batches using existing methods, as necessary to achieve comparable computational cost.

Subfields: Genetics, Molecular Biology

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Citations in the corpus

Fast two-stage phasing of large-scale sequence data. (2021, methodology): “The next major advance came from methods such as HAPI-UR, 21 SHAPEIT, 22 and EAGLE 23 that could analyze much larger datasets and whose computation time and memory scaled linearly or nearly linearly with sample size.”
The power of genetic diversity in genome-wide association studies of lipids (2021, methodology): “…following an iterative procedure starting with the most significant variant and grouping the surrounding region into a locus based on the larger of either ±500 kb or ±0.25 cM. cM positions were interpolated using the genetic map distributed with Eagle v.2.3.2 (genetic_map_hg19_withX.txt) 50 .”
Accurate, scalable and integrative haplotype estimation (2019, methodology): “Of note, the use of PBWT in the context of phasing was pioneered in Eagle2 3,4 in order to build compact representations of a ﬁ xed number of conditioning haplotypes (called HapHedge structures).”
Multiplexed droplet single-cell RNA-sequencing using natural genetic variation (2017, methodology): “Genotypes were imputed with EAGLE 57 and filtered for MAF > 0.2, resulting in a total of 189,322 SNPs. Cell type proportions were calculated as number of cells for each cell type divided by the number of total cells for each person.”
Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. (2019, methodology): “To enhance the speed of imputation, GWAS data are typically pre-phased, estimate haplotypes from genotyped markers in the cohort before beginning imputation, using programs like EAGLE (Loh et al., 2016) or SHAPEIT (Delaneau et al.”
Reference-based phasing using the Haplotype Reference Consortium panel (2016, methodology): “This paradigm targets a user group complementary to recent methods for phasing very large cohorts [13, 14].”