Intelligent Systems for Molecular Biology (ISMB)
About This Event
Visit us at our scientific poster presentation and meet our Genomic Experts.
Title: STAR-SEQR: A novel approach for detecting DNA breakpoints and RNA fusions from NGS data
Poster Number: G21
Displayed: Sunday, July 10, 10:00 a.m. through Monday, July 11, 2:30 p.m.
- Jeff Jasper, Senior Bioinformaticist
- Jason Powers, Ph.D., Manager of Bioinformatics and Clinical Systems Translational Genomics
- Victor Weigman, Ph.D. Associate Director Translational Genomics
Abstract: Genomic structural variation (SV) is a common clinical feature known to be involved in the initiation and pathogenesis of cancer. This complex class of variants also has significant implications on therapeutic decision and efficacy and has emerging roles in evidence-based clinical applications. However, despite recent advancements in the field, there is a lack of robust tools to accurately identify SVs from NGS data. Here we present STAR-SEQR, a novel tool used to detect and annotate DNA SVs and RNA fusions from paired-end sequencing data. This approach uses the popular STAR aligner as a first-pass approach to produce gapped junction and discordant paired reads. Additional filters include marking duplicates before assembling each candidate region, realignment and read-directionality checks to mitigate false-positive calls. Analytical testing has been performed on a set of samples with known DNA SVs including EML4-ALK, RET-CCDC6, and SLC34A2-ROS1 with 9 technical replicates of each. In every case STAR-SEQR accurately detected the breakpoint leading to 100% sensitivity and outperformed other software packages that were evaluated. Specificity was also 100% for these known samples. RNA fusions were evaluated against a synthetic dataset with every known fusion being detected. In summary, STAR-SEQR performs well in our testing and is currently being used in both the clinical and research settings