HAT: de novo variant calling for highly accurate short-read and long-read sequencing data

Abstract

Motivationde novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics studies (e.g., autism, epilepsy). ResultsHAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow begins with aligned read data (i.e., CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from short-read whole-exome sequencing, short-read wholegenome sequencing, and highly accurate long-read sequencing data. Availabilityhttps://github.com/TNTurnerLab/HAT Contacttychele@wustl.edu Supplementary informationSupplementary data are available at bioRxiv.