Experimental bias in metagenomics measurements

Microbiome measurements made via community sequencing (shotgun metagenomics or marker-gene sequencing) are currently inaccurate because existing experimental protocols are biased to measure some species 10-1000X more efficiently than others. As the different protocols used in different experiments enrich for different species, the measurements from different experiments are quantitatively incomparable. My current research aims to

• develop new methods to characterize bias from control experiments
• evaluate the effects of bias on microbiome analyses and diagnostics
• develop calibration methods to correct bias, making microbiome measurements accurate or at least quantitatively comparable across labs

This work is being carried out under the supervision of Ben Callahan at NC State and in collaboration with Amy Willis and David Clausen at the University of Washington. Our first effort was recently published in eLife; you can read a short summary here.

C. difficile ecology and pathogenesis

I provide bioinformatic support to efforts in the lab of Casey Theriot to study the ecology and pathogenesis of the gut pathogen C. difficile. Projects I am involved in include characterizing the prevalence of C. difficile in domestic animals and understanding the role of the gut microbiota in preventing C. difficile colonization and disease in domestic animals and in experimental mouse models.

Evolutionary dynamics

My PhD research used probabilistic mathematical modeling to study how spatial (geographic) structure affects the time it takes for a population to acquire a complex adaptation.