PopDel identifies medium-size deletions jointly in tens of thousands of genomes

Abstract

Thousands of genomic structural variants segregate in the human population and can impact phenotypic traits and diseases. Their identification in whole-genome sequence data of large cohorts is a major computational challenge. We describe a novel approach, PopDel, which jointly identifies deletions of about 500 to at least 10,000 bp in length in many genomes together. PopDel scales to tens of thousands of genomes as we demonstrate in evaluations on up to 49,962 genomes. We show that PopDel reliably reports common, rare and de novo deletions. On genomes with available high-confidence reference call sets PopDel shows excellent recall and precision. Genotype inheritance patterns in up to 6,794 trios indicate that genotypes predicted by PopDel are more reliable than those of previous SV callers. Furthermore, PopDels running time is competitive with the fastest tested previous tools. The demonstrated scalability and accuracy of PopDel enables routine scans for deletions in large-scale sequencing studies.