VisCap: inference and visualization of germ-line copy-number variants from targeted clinical sequencing data

Trevor J. Pugh, Sami S. Amr, Mark J. Bowser, Sivakumar Gowrisankar, Elizabeth Hynes, Lisa M. Mahanta, Heidi L. Rehm, Birgit Funke, Matthew S. Lebo
2015 Genetics in Medicine  
Purpose: To develop and validate VisCap, a software program targeted to clinical laboratories for inference and visualization of germ-line copy-number variants (CNVs) from targeted nextgeneration sequencing data. Methods: VisCap calculates the fraction of overall sequence coverage assigned to genomic intervals and computes log2 ratios of these values to the median of reference samples profiled using the same test configuration. Candidate CNVs are called when log2 ratios exceed user-defined
more » ... holds. Results: We optimized VisCap using 14 cases with known CNVs, followed by prospective analysis of 1,104 cases referred for diagnostic DNA sequencing. To verify calls in the prospective cohort, we used droplet digital polymerase chain reaction (PCR) to confirm 10/27 candidate CNVs and 72/72 copy-neutral genomic regions scored by VisCap. We also used a genome-wide bead array to confirm the absence of CNV calls across panels applied to 10 cases. To improve specificity, we instituted a visual scoring system that enabled experienced reviewers to differentiate true-positive from false-positive calls with minimal impact on laboratory workflow. Conclusions: VisCap is a sensitive method for inferring CNVs from targeted sequence data from targeted gene panels. Visual scoring of data underlying CNV calls is a critical step to reduce false-positive calls for follow-up testing. Genet Med advance online publication 17 December 2015
doi:10.1038/gim.2015.156 pmid:26681316 pmcid:PMC4940431 fatcat:4xhpvy452vefzhvrujp7un5o7m