Skip to main content
Skip to main menu Skip to spotlight region Skip to secondary region Skip to UGA region Skip to Tertiary region Skip to Quaternary region Skip to unit footer

Slideshow

Amy Willis

Amy Willis
Amy Willis
University of Washington
Caldwell Hall Room 102

Estimating diversity and relative abundance in microbial communities

High-throughput sequencing has advanced our understanding of the role that bacteria and archaea play in marine, terrestrial and host-associated health. Microbial community ecology differs in many ways from macroecology, and therefore new statistical methods are required to analyze microbiome data. In this talk I will present two new statistical methods for the analysis of microbiome data. The first, DivNet, estimates the diversity of microbial communities, and the second, corncob, estimates the relative abundance of microbial strains, metabolites, or genes. Both methods explicitly model microbe-microbe interactions, resulting in larger (but more accurate) estimates of variance compared to classical models. The methods will be illustrated with an analysis of the effects of wildfire on soil microbial communities in the northwestern Canadian boreal forest. 

Support us

We appreciate your financial support. Your gift is important to us and helps support critical opportunities for students and faculty alike, including lectures, travel support, and any number of educational events that augment the classroom experience. Click here to learn more about giving.

Every dollar given has a direct impact upon our students and faculty.