UPCOMING ASA-SSGG SHORT COURSE SERIES: A Practical Introduction to Microbiome Data Analysis
Course Instructors: Dr. Michael C. Wu and Dr. Ni Zhao
TA: Dr. Shilan Li
February 04, 06, 11 and 13, 2025. Noon to 2:00 PM (EST)
(4 x 2-Hour Live Sessions over Two Weeks)
Registration link: https://amstat.users.membersuite.com/events/2e04bc98-0078-c57d-bcd2-0b47a6a88cc4/details
Registration Fee: ASA Student Member $75; SSGG Member $95; ASA Member $110; External participant (non-ASA member) $170
Course abstract
The microbiome plays a fundamental role in human health and diseases, influencing a wide range of conditions from cardiovascular disease to mental health disorders. Recently developed technologies such as 16S rRNA sequencing and shotgun metagenomics sequencing are now routinely employed in large epidemiological studies and clinical investigations to assess the impact of the microbiome. This has spurred the development of statistical and analytical advancements which have adopted approaches from other “omics” fields as well as created de novo tools specifically designed to address the unique characteristics of microbiome data.
This short course aims to provide a practical introduction to key concepts and methodologies used in microbiome data analysis. We will cover topics including bioinformatic tools and standard statistical methodologies including those for community-level analysis, individual taxon analysis, and data integration. The course will focus on the most commonly used methods in practice, offering hands-on experience with example data sets and reproducible code.
This course is designed for participants who have a basic understanding of statistics and epidemiology and are familiar with R or Python programming. Detailed knowledge of the microbiome is not assumed. Emphasis is on the practical deployment of contemporaneous methods.
Syllabus (45 minutes lecture and 45 minutes hands-on tutorial)
- February 4th: Overview of microbiome research
Covered Topics: Basic terminology, 16s rRNA sequencing technology, shotgun metagenomics sequencing technology, data preprocessing, DADA2, Qiime2 pipeline, OTUs, ASVs, phylogeny, and taxonomy
- February 6th: Community-level analysis of microbiome
Covered Topics: alpha diversity, beta diversity, data visualization, waterfall plot, PCOA, biplot, community level analysis (PERMANOVA, MiRKAT);
- February 11th: Taxa differential abundance analysis
Covered Topics: Classes of statistical approaches, strongly parametric methods, nonparametric methods, zero inflation, compositional approaches, ANCOM, ANCOM-BC, DESeq2
- February 13th: Microbiome data integration
Covered Topics: Vertical Integration via Batch Effect adjustment (ConQuR) and mixed effect model, Horizontal Integration (co-inertia analysis, CCA) with multiple omics, mediation analysis
Learning objectives
- To explore the landscape of microbiome research and understand the unique challenges and characteristics associated with microbiome data.
- To grasp the underlying concepts and statistical foundations of some of the most widely used tools and software for microbiome data analysis.
- To acquire hands-on experience in analyzing microbiome data.
Course instructors’ backgrounds
Michael Wu is a Professor in the Biostatistics Program at the Fred Hutchinson Cancer Center and an Affiliate Professor in the Department of Biostatistics at the University of Washington. His primary research interest lie in developing and applying cutting-edge statistical tools for microbiome analysis. Many of the tools from his group represent integral parts of current analytic pipelines, including the MiRKAT and ConQuR approaches. Dr. Wu is an elected Fellow of the American Statistical Association (ASA) and the former chair of the ASA Section on Statistics in Genomics and Genetics.
Ni Zhao is an Associate Professor of Biostatistics at the Bloomberg School of Public Health at Johns Hopkins University. Dr. Zhao has extensive experience developing and applying statistical methodologies for large-scale microbiome research. Her recent work focuses on creating innovative analytical tools to address the unique and pressing challenges in microbiome studies, particularly in understanding and mitigating biases and batch effects in microbiome association studies and integrating microbiome data with other ‘omics’ data. Dr. Zhao is a recipient of the ASA W.J. Youden Award.
Course TA’s background
Shilan Li is a postdoctoral fellow in the Department of Biostatistics at the Bloomberg School of Public Health, Johns Hopkins University, under the mentorship of Dr. Ni Zhao. Dr. Li earned her PhD in Biostatistics from Georgetown University and served as a Predoctoral Trainee at the National Cancer Institute. She has extensive experience in analyzing large-scale microbiome studies, including projects from the National Health and Nutrition Examination Survey (NHANES) and the Environmental influences on Child Health Outcomes (ECHO) program.
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Previous short courses
The recordings for some previous short courses can be accessed through the members-only site. To access, please log in and travel to the past short courses tab. If you are not a section member yet, you may join us through Join – Section on Statistics in Genomics and Genetics (amstat.org).
- February 2024: Introduction to Mendelian Randomization (Dr. Jingshu Wang, Dr. Ting Ye, Dr. Neil M Davies, and Dr. Jean Morrison)
- April 2023: Selective Introduction to Multi-Omics Analysis (Dr. George Tseng, Dr. Katerina Kechris, Rick Chang, Sierra Niemiec, Dr. Jack Pattee, and Wenjia Wang)
- January 2022: An Introduction to Deep Learning in Omics (Dr. Wei Sun and Dr. Nancy Zhang)