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Abel, H. J.

Publications and source records attributed to Abel, H. J..

2 recordsLinked to original sources

svtools: population-scale analysis of structural variation

SummaryLarge-scale human genetics studies are now employing whole genome sequencing with the goal of conducting comprehensive trait mapping analyses of all forms of genome variation. However, methods for structural variation (SV) analysis have lagged far behind those for smaller scale variants, and there is an urgent need to develop more efficient tools that scale to the size of human populations. Here, we present a fast and highly scalable software toolkit (svtools) and cloud-based pipeline for assembling high quality SV maps - including deletions, duplications, mobile element insertions, inversions, and other rearrangements - in many thousands of human genomes. We show that this pipeline achieves similar variant detection performance to established per-sample methods (e.g., via LUMPY), while providing fast and affordable joint analysis at the scale of [≥]100,000 genomes. These tools will help enable the next generation of human genetics studies.\n\nAvailability and Implementationsvtools is implemented in Python and freely available (MIT) from https://github.com/hall-lab/svtools.\n\nContactihall@wustl.edu

bioinformatics

Exome sequencing identifies high impact trait-associated alleles enriched in Finns

As yet undiscovered rare variants are hypothesized to substantially influence an individuals risk for common diseases and traits, but sequencing studies aiming to identify such variants have generally been underpowered. In isolated populations that have expanded rapidly after a population bottleneck, deleterious alleles that passed through the bottleneck may be maintained at much higher frequencies than in other populations. In an exome sequencing study of nearly 20,000 cohort participants from northern and eastern Finnish populations that exemplify this phenomenon, most novel trait-associated deleterious variants displayed frequencies 10-173 times higher than in other European populations. These enriched alleles underlie 30 novel associations with 20 disease-related quantitative traits and demonstrate a geographical clustering equivalent to that of Mendelian disease mutations characteristic of the Finnish population. Sequencing studies in populations without this unique history would require hundreds of thousands to millions of participants for comparable power.

genomics