Engineering Commons^™

Ultrasensitive Detection Of Rare Mutations Using Next-Generation Targeted Resequencing, Patrick Flaherty, Georges Natsoulis, Omkar Muralidharan, Mark Winters, Jason Buenrostro, John Bell, Sheldon Brown, Mark Holodniy, Nancy Zhang, Hanlee P. Ji

Mathematics and Statistics Department Faculty Publication Series

With next-generation DNA sequencing technologies, one can interrogate a specific genomic region of interest at very high depth of coverage and identify less prevalent, rare mutations in heterogeneous clinical samples. However, the mutation detection levels are limited by the error rate of the sequencing technology as well as by the availability of variant-calling algorithms with high statistical power and low false positive rates. We demonstrate that we can robustly detect mutations at 0.1% fractional representation. This represents accurate detection of one mutant per every 1000 wild-type alleles. To achieve this sensitive level of mutation detection, we integrate a high accuracy …