Multiplexing methods to reduce sequencing costs.

Coral Genomics, Inc., San Francisco CA

Investigators

Abstract

Project Summary As the capacity of next generation sequencing machines has increased, the marginal cost of shallow sequencing has become much higher than that of deep sequencing. For the development of novel protocols, quality checking, and targeted clinical sequencing, sequencing demand is often far less than an entire sequencing run. This issue can be resolved if a user can find a partner performing a high depth sequencing run to ?spike? their library into. By pooling samples together, both users can save considerably on sequencing costs. However, this process of finding sequencing partners is subject to local availability of sequencing supply and demand. Moreover, variation in representation due to user error and library specific biases can reduce the efficiency of the pooling. An integrated platform for sample pooling called WeSeq is proposed. The primary goal of WeSeq is to maximize the time and cost efficiency of next generation sequencing. WeSeq develops algorithms to quickly turnaround sequencing analysis results to end users and to minimize the representation biases associated with pooling large numbers of diverse libraries together. We develop enzymatic approaches for greatly increasing DNA barcoding capacity and for reducing the number of sequencing required for applications such as single cell RNA-seq. Ultimately, we hope ot make next-generation sequencing affordable and fast enough for it to become routine in research and clinical applications.