A Benchmark of Modern Statistical Phasing Methods
Beck, A. T.; Kang, H. M.; Zoellner, S.
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Modern statistical phasing methods efficiently and accurately infer haplotype phase in large genomic samples, and their performance is critical for downstream analyses. However, rigorously evaluating phasing accuracy remains challenging. Here we demonstrate the use of synthetic diploids generated from male X chromosome sequences to benchmark and compare three commonly-used phasing methods (Beagle 5.4, SHAPEIT 5.1.0, and Eagle v2.4.1). While errors across methods are highly correlated, we observe overall higher rate of errors in Eagle. When contrasting switch error and flip (double-switch) errors, switch rates are higher in Eagle, whereas flip rates are higher in SHAPEIT. These patterns ae consistent across populations. For all methods we observe an enrichment of errors at both CpG sites and rare variant sites, with a stronger enrichment for flip errors. We compare these error estimates with estimates from Mendelian-resolved trio probands: single switch error rates observed in X chromosome synthetic diploids are consistent with those observed in all autosomes, with higher rates of double switch errors in the autosomes than in X.
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