Use of RAPTR-SV to identify SVs from read pairing and split read signatures

Abstract

High-throughput short read sequencing technologies are still the leading cost-effective means of assessing variation in individual samples. Unfortunately, while such technologies are eminently capable of detecting single nucleotide polymorphisms (SNP) and small insertions and deletions, the detection of large copy number variants (CNV) with these technologies is prone to numerous false positives. CNV detection tools that incorporate multiple variant signals and exclude regions of systemic bias in the genome tend to reduce the probability of false positive calls and therefore represent the best means of ascertaining true CNV regions. To this end, we provide instructions and details on the use of the RAPTR-SV CNV detection pipeline, which is a tool that incorporates read-pair and split-read signals to identify high confidence CNV regions in a sequenced sample. By combining two different structural variant (SV) signals in variant calling, RAPTR-SV enables the easy filtration of artifact CNV calls from large datasets.