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

MOTIVATION

variant (DNV) calling is challenging from parent-child sequenced trio data. We developed are nd ortoise (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).

RESULTS

HAT 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 whole-genome sequencing, and highly accurate long-read sequencing data.