Utility of Next Generation Sequencing Data for Rare Variant Detection and Identification in a Bacterial Sample

Award Information
Agency: Department of Homeland Security
Branch: N/A
Contract: N10PC20199
Agency Tracking Number: 1011114
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: N/A
Solicitation Topic Code: H-SB010.1-002
Solicitation Number: N/A
Small Business Information
Eureka Genomics
750 Alfred Nobel Drive, #108, Hercules, CA, 94547-
DUNS: 808461664
HUBZone Owned: Y
Woman Owned: Y
Socially and Economically Disadvantaged: Y
Principal Investigator
 Vacheslav Fofanov
 (713) 357-9587
 vyfofanov@eurekagenomics.com
Business Contact
 Didier Perez
Title: President
Phone: (415) 269-0666
Email: didier@eurekagenomics.com
Research Institution
N/A
Abstract

 

The long-term objective is to develop a statistically sound rare variant (SNPs) detection and SNP profile comparison method, based on high throughput sequencing (HTS) and advanced bioinformatics, that is capable of detecting a mutations present in as low as 1/5000 bacterial cells in the sample. This will be accomplished in five tasks: (1) Develop and test a statistical model to predict sample coverage required to detect SNPs in a strain of given rarity with pre-specified level of confidence. (2) Determine the ability to use HTS reads to assign SNPs to correct rare variants (3) Quantify the effect of limitations of the sequencing platform on rare variant detection (4) Develop a statistical framework to compare SNP profiles, (5) Develop a research plan for Phase II.  Rare variant detection and matching will be important for prosecution of bioterrorism attacks or attempts. The commercial opportunity of the forensic application is unknown, but commercial applications in clinical diagnostics associated with the detection of drug resistant variants are extensive. There is an urgent need (estimated 100M USD US market annually) for a diagnostic test to identify the presence of multi- or extensively- drug resistant tuberculosis present in 1 percent or less of the sample.

* information listed above is at the time of submission.

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