Haplotype-aware diplotyping from noisy long reads

Genome Biology

Tobias Marschall¹  Jana Ebler¹  Marina Haukness²  Benedict Paten²  Trevor Pesout² 

[1] Center for Bioinformatics, Saarland University;UC Santa Cruz Genomics Institute, University of California Santa Cruz;

关键词: Computational genomics;    Long reads;    Genotyping;    Phasing;    Haplotypes;    Diplotypes;   

DOI  :  10.1186/s13059-019-1709-0

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown