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Haplotype-aware diplotyping from noisy long reads

Authors: Jana Ebler; Marina Haukness; Trevor Pesout; Tobias Marschall; Benedict Paten;

Haplotype-aware diplotyping from noisy long reads

Abstract

SNP calls for individual NA12878 produced by MarginPhase and WhatsHap on PacBio and Oxford Nanopore data as well as the version of source code used to generate this dataset. Paper Abstract: Current genotyping approaches for single nucleotide variations rely on short, accurate reads from second generation sequencing devices. Presently, third generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort. Source Code: WhatsHap: bitbucket.org/whatshap/whatshap MarginPhase: github.com/benedictpaten/marginPhase

Keywords

Genotyping, Models, Statistical, Genotyping Techniques, QH301-705.5, Phasing, Method, Genomics, Long reads, QH426-470, Diplotypes, Computational genomics, Haplotypes, Genetics, Computational genomics, long-reads, genotyping, phasing, diplotypes, Biology (General), Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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