I-Corps: Software for the Next Generation Sequence Analysis for Homogeneous Populations

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The broader impact/commercial potential of this I-Corps project is improving public health systems by predicting, monitoring, and preventing outbreaks of infectious diseases. The broader applications of the proposed software system for analysis of sequencing data will also include tracing cancer development and analyzing its potential to grow, mutate, and resist treatment. The proposed software system will be integrated into laboratories' pipelines for clustering and assembling sequencing reads into complete genomic sequences. The proposed statistical algorithms will analyze the sequencing data more accurately which improves sequencing quality without an increase in sequencing depth thus further reducing sequencing cost. The proposed software system will attract epidemiological and medical laboratories by more accurate analysis and cost reduction of high-throughput sequencing.This I-Corps project deals with growing demand for powerful computational tools for analyzing high-throughput sequencing data. Existing software tools can successfully extract different sequences form the same sample but, in many applications, (such as an investigation of outbreaks of infectious disease, cancer research, and genome-wide association studies) it is necessary to distinguish multiple distinct yet closely related genomic sequences. The main obstacle for such studies is a high sequencing error rate and short length of reads produced by high-throughput sequencing technologies. The proposed software system can overcome these obstacles by using statistical algorithms capable of sorting out the sequencing errors delivering complete genomic sequences and accurately identifying point mutations distinguishing closely related sequences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.