HAPDeNovo: a haplotype-based approach for filtering and phasing de novo mutations in linked read sequencing data.

ABSTRACT:

Background

De novo mutations (DNMs) are associated with neurodevelopmental and congenital diseases, and their detection can contribute to understanding disease pathogenicity. However, accurate detection is challenging because of their small number relative to the genome-wide false positives in next generation sequencing (NGS) data. Software such as DeNovoGear and TrioDeNovo have been developed to detect DNMs, but at good sensitivity they still produce many false positive calls.

Results

To address this challenge, we develop HAPDeNovo, a program that leverages phasing information from linked read sequencing, to remove false positive DNMs from candidate lists generated by DNM-detection tools. Short reads from each phasing block are allocated to each of the two haplotypes follow

SUBMITTER: Zhou X 

PROVIDER: S-EPMC6006847 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature