Advancements in next-generation sequencing (NGS) technologies have produced massive number of short read sequences, making secondary analysis a challenging big data problem. In this seminar presented at Molecular Tri-Con 2016, Bina’s Senior Director of Bioinformatics, Hugo Lam, shared current approaches at Bina in assessing and improving the accuracy of NGS algorithms. Specifically, he touched on how Bina's research expanded the benchmarking toolset through the availability of a better gold set and a variant simulation and validation framework.
A high-confidence, comprehensive human variant set is critical in assessing the accuracy of sequencing algorithms, which are crucial for precision-based medicine and clinical diagnostics. Although recent research has attempted to provide such a resource, it still does not encompass all major types of variants, in particular structural variants (SVs) that have been linked to debilitating diseases.