Time：2:00pm, December 17th, 2015

Venue：Middle Meeting Room, Level 4, Building 5

 

Abstract:

    The high-throughput sequencing technologies have provided a powerful tool to study the microbial organisms living in various environments including ocean water, soil, and the human body. Characterizing microbial interactions can give us insights into how they live and work together as a community. Metagonomic data are usually summarized in a compositional fashion due to varying sampling/sequencing depths from one sample to another. We study the interaction patterns of microbial organisms using their relative abundance information. Analyzing compositional data using conventional correlation methods has been shown prone to bias that leads to artifactual correlations. We propose a novel method, REBACCA, to identify significant co-occurrence patterns by finding sparse solutions to a system with a deficient rank. To be specific, we construct the system using log ratios of count or relative abundance data and solve the system using the regularized l1-norm shrinkage method. Our comprehensive simulation studies show that REBACCA achieves higher accuracy in general when a sparse condition is satisfied and runs considerably faster than the existing comparable method. The current statistical and computational methods that are being developed to analyze the metagnoimcs data and the challenges will also be highlighted in the talk.

 

Biography:

    Hongmei Jiang is an Associate Professor in the Department of Statistics at Northwestern University. She received her Ph.D. In Statistics from Purdue University. Her research interest includes developing statistical methods and computational algorithms for high throughput genomic and metagenomic data, multiple comparisons and multiple tests, and high dimensional variable selection. Prof.Jiang is the guest editor of Cancer Informatics and reviewer for several statistics and bioinformatics journals.As a PI and co-PI on National Science Foundation (NSF) funded grants and Chicago Biomedical Consortium, and as a co-Investigator on several National Institutes of Health (NIH) funded grants, She has successfully carried out the projects, and produced several peer-reviewed publications from each project.