Pancreatic Neuroendocrine Tumors (PNETs) are a rare but clinically important form of cancer. Because many PNETs grow silently and are therefore frequently diagnosed at a late stage, approximately 65% of patients present with unresectable or metastatic disease. As a result, these patients have a poor prognosis and a median survival time of 24 months with limited treatment options.
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.