TY - JOUR T1 - Samplot: A Platform for Structural Variant Visual Validation and Automated Filtering JF - bioRxiv DO - 10.1101/2020.09.23.310110 SP - 2020.09.23.310110 AU - Jonathan R. Belyeu AU - Murad Chowdhury AU - Joseph Brown AU - Brent S. Pedersen AU - Michael J. Cormier AU - Aaron R. Quinlan AU - Ryan M. Layer Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/09/26/2020.09.23.310110.abstract N2 - Visual validation is an essential step in structural variant (SV) detection to eliminate false positives. We present Samplot, a tool for quickly creating images that display the read depth and sequence alignments necessary to adjudicate purported SVs across multiple samples and sequencing technologies, including short, long, and phased reads. These simple images can be rapidly reviewed to curate large SV call sets. Samplot is easily applicable to many biological problems such as prioritization of potentially causal variants in disease studies, family-based analysis of inherited variation, or de novo SV review. Samplot also includes a trained machine learning package that dramatically decreases the number of false positives without human review. Samplot is available via the conda package manager or at https://github.com/ryanlayer/samplot.Competing Interest StatementThe authors have declared no competing interest. ER -