XHap: haplotype assembly using long-distance read correlations learned by transformers.

ABSTRACT:

Summary

Reconstructing haplotypes of an organism from a set of sequencing reads is a computationally challenging (NP-hard) problem. In reference-guided settings, at the core of haplotype assembly is the task of clustering reads according to their origin, i.e. grouping together reads that sample the same haplotype. Read length limitations and sequencing errors render this problem difficult even for diploids; the complexity of the problem grows with the ploidy of the organism. We present XHap, a novel method for haplotype assembly that aims to learn correlations between pairs of sequencing reads, including those that do not overlap but may be separated by large genomic distances, and utilize the learned correlations to assemble the haplotypes. This is accomplished by leveraging trans

SUBMITTER: Consul S 

PROVIDER: S-EPMC10713121 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature