Workshop in Biostatistics

DATE: November 19, 2015
TIME: 1:30 - 2:50 pm
LOCATION: Medical School Office Building, Rm x303
TITLE: Statistical Challenges in the study of stability in the Human Microbiome
SPEAKER: Susan Holmes
Professor, Statistics and BioX
John Henry Samter University Fellow
coDirector, Math Comp Sci, Stanford


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 different 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.

This contains joint work with Joey McMurdie, Ben Callahan, Julia Fukuyama, Kris Sankaran and David Relman's Lab members from Stanford.

Suggested readings:
Paul J McMurdie, Susan Holmes (2014). Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible. PLOS Computational Biology, Methods Section.

Daniel B. DiGiulio, Benjamin J. Callahan, Paul J. McMurdie, Elizabeth K. Costello, Deirdre J. Lyell, Anna Robaczewska, Christine L. Sun, Daniela S. A. Goltsman, Ronald J. Wong, Gary Shaw, David K. Stevenson, Susan P. Holmes, and David A. Relman. Temporal and spatial variation of the human microbiota during pregnancy. PNAS 2015 ; published ahead of print August 17, 2015, doi:10.1073/pnas.1502875112 [Journal PDF with Supplementary] [Reproducible Research: Rmd files and RData]

McMurdie, P.J. & Holmes, S.P. (2013). phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLOS ONE, April 22, 2013.

Fukuyama, J., McMurdie, P.J., Dethfelsen, L., Relman, D. and Holmes, S.P. (2012). Comparisons of Distance Methods for Combining Covariates and Abundances in Microbiome Studies. Pac Symp Biocomput 2012:213-24.