STA 290 Seminar Series
Thursday, November 12th, 4:10pm, MSB 1147 (Colloquium Room)
Refreshments at 3:30pm in MSB 4110 (Statistics Lounge)
Speaker: Susan Holmes (Stanford University)
Title: Analyzing data from perturbation experiments: the case of the human microbiome
Abstract: The human microbiome is a complex assembly of bacteria that are sensitive to many perturbations. We have developed specific tools for studying the vaginal, intestinal and oral microbiomes under many using time course data following many different types of perturbations (pregnancy, hypo-salivation inducing medications and antibiotics are some examples).
A suite of statistical tools written in R based on a Bioconductor package (phyloseq) allows for easy normalization, visualization and statistical testing of the longitudinal multi-table data composed of 16sRNA reads combined with clinical data, transcriptomic and metabolomic profiles. Challenges we have had to address include information leaks, the heterogeneity of the data, multiplicity of choices during the analyses and validation of results. A first step forward has been made through development of carefully designed normalization procedures. We have now used this statistical framework to study the stability of the human microbiome in pregnancy and predict preterm birth from certain microbial community biomarkers.
This contains joint work with Joey McMurdie, Ben Callahan, Julia Fukuyama, Kris Sankaran and David Relman's Lab members from Stanford.