A comprehensive benchmarking of WGS-based structural variant callers

Sarwal, V.; Niehus, S.; Ayyala, R.; Chang, S.; Lu, A.; Darci-Maher, N.; Littman, R.; Wesel, E.; Castellanos, J.; Chikka, R.; Distler, M. G.; Eskin, E.; Flint, J.; Mangul, S.

doi:10.1101/2020.04.16.045120

bioRxiv · 10.1101/2020.04.16.045120

A comprehensive benchmarking of WGS-based structural variant callers

Sarwal, V.·Niehus, S.·Ayyala, R.·Chang, S.·Lu, A.·Darci-Maher, N.·Littman, R.·Wesel, E.·Castellanos, J.·Chikka, R.·Distler, M. G.·Eskin, E.·Flint, J.·Mangul, S.

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Abstract

Advances in whole genome sequencing promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from whole genome sequencing (WGS) data presents a substantial number of challenges and a plethora of SV-detection methods have been developed. Currently, there is a paucity of evidence which investigators can use to select appropriate SV-detection tools. In this paper, we evaluated the performance of SV-detection tools using a comprehensive PCR-confirmed gold standard set of SVs. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of SV-detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance, as the SV-detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV-detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low and ultra-low pass sequencing data.

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Sarwal, V., Niehus, S., Ayyala, R., Chang, S., Lu, A., Darci-Maher, N., Littman, R., Wesel, E., Castellanos, J., Chikka, R., Distler, M. G., Eskin, E., Flint, J., Mangul, S.. 2020-04-18. A comprehensive benchmarking of WGS-based structural variant callers. https://doi.org/10.1101/2020.04.16.045120

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