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SV-BET: Structure Variation Benchmarking and Evaluation Tool with Comparative Analysis of Split Read-Based Approaches

Eman A. Alzaid 1 and Ghada Badr 1,2
1. King Saud University, Riyadh, Saudi Arabia
2. IRI- The City of Scientific Research and Technological Applications, University and Research District, P.O. 21934, New Borg Alarab, Alexandria, Egypt
Abstract—Several structural variation identification approaches have been developed with various considerations and merits. As a scientist, it is important to choose the suitable tool. Unfortunately, there is a lack of gold standards to benchmark these approaches. A Structural Variation Benchmarking and Evaluation Tool (SV-BET) is proposed, which composed of three main components: benchmark creator, mapper, and evaluator. We use the proposed tool to evaluate the performances of seven available approaches: Pindel, Prism, Delly, Softsearch, Softsv, Socrates, and Manta. These tools are based on split-read-based approaches for detecting structural variations. SVBET is tested using the Escherichia coli K12 genome. Results show the sensitivity and positive-predictive value of detected structural variations and breakpoints for each approach. SV-BET can be used to evaluate the performance of other SV identification algorithms.

Index Terms—structural variation, split-read, breakpoints, next generation-sequencing

Cite: Eman A. Alzaid and Ghada Badr, "SV-BET: Structure Variation Benchmarking and Evaluation Tool with Comparative Analysis of Split Read-Based Approaches," International Journal of Pharma Medicine and Biological Sciences, Vol. 5, No. 4, pp. 217-221, Octorber 2016. doi: 10.18178/ijpmbs.5.4.217-221


 
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