Improved non-human variant calling using species-specific DeepVariant models

In this work, we investigate variant calling across a pedigree of mosquito (Anopheles gambiae) genomes. Using rates of Mendelian violation, we assess pipelines developed to call variation in humans when applied to mosquito samples. We demonstrate the ability to rapidly retrain DeepVariant without the need for a gold standard set by using sites that are consistent versus inconsistent with Mendelian inheritance. We show that this substantially improves calling accuracy by tuning DeepVariant for the new genome context. Finally, we generate a model for accurate variant calling on low-coverage mosquito genomes and a corresponding variant callset.

• Machine Intelligence

• Health & Bioscience