Faculty Candidate 2014

Computational Challenges in Microbial Forensics at the Ultra Rare Variant Level

When: Wednesday, March 5, 2014
Where: PGH 232
Time: 11:00 AM

Speaker: Dr. Viacheslav Y. Fofanov, Eureka Genomics Corporation

Host: Prof. Ioannis Pavlidis

Identification of ultra rare variants (those present down to 0.1% frequency) within relatively homogeneous biological samples, such as single-species bacterial or viral populations, is important in many fields, including forensics, infectious disease diagnostics, biodefense, and quality control of biological products.  Recent advances in High Throughput Sequencing (HTS) allows sensitive detection of variants at previously unattainable frequencies, but come with their own computational, statistical, and biological challenges.  One of the significant impediments to microbial forensics are biases/errors introduced at every step of the rare variant detection process: from DNA fragmentation and sequencing errors to mapping algorithm and SNP calling methods.  This talk will focus on the challenges and potential solutions associated with novel rare variant detection approach, developed by our group, for detecting variants present in as low as 0.1% frequency in a bacterial population.

Bio:
Viacheslav Fofanov has received his Ph.D. in Statistics from Rice University in 2008.  Since then, he has been leading a Bioinformatics Department for Eureka Genomics Corporation.  In that capacity, he has been building successful research teams, heading independent research projects, and attracting federal research funding, both as a PI and as a member of collaborative research teams supporting investigators on NIH and DHS grants.  The primary focus of Dr. Fofanov's research is Bioinformatics and Statistics, with a focus on developing algorithms and statistical methods for the analysis of Large Data sets, including applications of High Throughput Sequencing to the characterization of complex environmental and clinical samples, pathogen detection, and identification of rare variants in bacterial and viral populations.