Susan Holmes

About

Susan Holmes is a Professor of Statistics, Emerita, at Stanford University. She has been working in non-parametric multivariate statistics applied to Biology since 1985. Holmes trained in the French school of Data Analysis in Montpellier and has taught at MIT, Harvard, and was an Associate Professor of Biometry at Cornell before moving to Stanford in 1998. She created the Thinking Matters class: Breaking Codes and Finding Patterns and enjoys working on big messy data sets, primarily from the areas of Immunology, Cancer Biology, and Microbial Ecology. Her theoretical interests include applied probability, Monte Carlo Markov chains (MCMC), Graph Limit Theory, Differential Geometry, and the topology of the space of Phylogenetic Trees. Holmes co-authored the book Modern Statistics for Modern Biology with Wolfgang Huber from EMBL and teaches this material as a crash course (BIOS221) regularly every year. Her current research focus is on improving the statistical analyses and reproducibility of data in perturbation studies of the Human Microbiome. She holds numerous honors and awards, including fellowships at the Fields Institute and the Center for the Advanced Study of the Behavioral Sciences, and has served on various scientific advisory boards and research institutes.

Research topics

• Computer Science
• Medicine
• Immunology
• Biology
• Internal medicine
• Pathology
• Mathematics
• Data Mining
• Data science
• Intensive care medicine

Selected publications

• Variability in the analysis of a single neuroimaging dataset by many teams

  Nature · 2020 · 1174 citations

  DOI

• Reporting guidelines for human microbiome research: the STORMS checklist

  Nature Medicine · 2021 · 452 citations

  The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-ind…

  DOI

• Cytokine profile in plasma of severe COVID-19 does not differ from ARDS and sepsis

  JCI Insight · 2020 · 272 citations

  BACKGROUNDElevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.METHODSWe used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting s…

  DOI

• Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19

  The Journal of Experimental Medicine · 2021 · 228 citations

  Our understanding of protective versus pathological immune responses to SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is limited by inadequate profiling of patients at the extremes of the disease severity spectrum. Here, we performed multi-omic single-cell immune profiling of 64 COVID-19 patients across the full range of disease severity, from outpatients with mild disease to fatal cases. Our transcriptomic, epigenomic, and proteomic analyses revealed widespread dysfunct…

  PublisherOA PDFDOI

• Geomstats: A Python Package for Riemannian Geometry in Machine Learning

  arXiv (Cornell University) · 2020 · 97 citations

  We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matrices, Lie groups of transformations, and many more. We provide object-oriented and extensively unit-tested implementations. Among others, manifolds come equipped with families of Riemannian metrics, with associated exponential and logarithmic maps, geodesics and parallel transport. Statistics and learning algorithms pro…

  DOI

Recent grants

• EMSW21-VIGRE: Vertical Integration of Mathematics, Statistics and Applied Mathematics.

  NSF · $2.7M · 2005–2014

• NIH Grant R03AI063576

  NIH · $149k · 2010

• Hierarchical Testing

  NSF · $300k · 2012–2015

Frequent coauthors

• Catherine A. Blish

  Chan Zuckerberg Initiative (United States)

  85 shared

• David A. Relman

  Stanford University

  67 shared

• Heather B. Jaspan

  University of Cape Town

  48 shared

• Persi Diaconis

  48 shared

• Christof Seiler

  Maastricht University

  45 shared

• Clive M. Gray

  University of Cape Town

  44 shared

• Anna‐Ursula Happel

  University of Cape Town

  37 shared

• Jonathan M. Blackburn

  University of Cape Town

  37 shared

Labs

• Susan HolmesPI

Awards & honors

• CASBS Fellow, Center for the Advanced study of the Behaviora…
• Breiman Lecturer, N(eur)IPS (December, 2016)
• Fellow, Fields Institute in Mathematical Sciences, Toronto,…
• Director's Transformative Research Award, NIH (2013)
• John Henry Samter University Fellow in Undergraduate Educati…

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