The long-term objective is to develop a rare variant (SNPs) detection pipeline, based on high throughput sequencing (HTS) and advanced bioinformatics, with the goal of detecting mutations present in ratio as low as 1:1000. To achieve this goal, we propose to: (1) Develop statistical and computational approaches to evaluate the effects of sequencing platform, target genome, and mapping algorithm on the accuracy of the rare variant detection. (2) Implement and deliver rare variant detection pipeline. (3) Experimentally validate the implemented rare variant detection pipeline, culminating a full scale B. anthracis case study. (4) Develop a software application to automatically acquire defined in task 1 statistical characteristics of errors associated with instruments, platforms, library preparation protocols, and sequencing chemistry, which can affect the overall accuracy of the rare variant detection. Rare variant detection is important for prosecution of bioterrorism attacks or attempts. While, the commercial opportunity of the forensic application is unknown, the commercial applications in clinical diagnostics associated with the detection of drug resistant variants such as diagnostic test to identify the presence of multi- or extensively- drug resistant tuberculosis present in less than 1 percent of the sample are significant.
