MaAsLin 3 for Microbiome Statistics and Epidemiology

02/20/25

17:00 CET

Join us for an enlightening session with Dr Curtis Huttenhower, a leader in computational biology and the lead author behind MaAsLin 3, as he delves into the transformative capabilities of this next-generation statistical tool for microbiome research.

 

What You’ll Learn:

 

The Science Behind MaAsLin 3:

Gain a comprehensive understanding of how MaAsLin 3 addresses the challenges of differential abundance analysis for microbial communities. Learn about its statistical foundations, key innovations, and why it stands out as an analysis tool for microbiome analytics.

 

Key Features and Advancements:

MaAsLin enables differential abundance analysis using mixed linear models, supporting complex metadata, experimental designs, and addressing statistical properties of microbiome data such as sparsity and compositionality. MaAsLin 3 adds new capabilities for sparsity modeling, compositional normalization, spike-ins, and new model designs.

 

Applications Across Disciplines:

Discover how MaAsLin 3 is being applied in diverse fields such as clinical microbiome research, environmental studies, and industrial biotechnology. Learn how it empowers researchers to uncover meaningful insights from complex datasets.

 

Future Directions and Q&A with Dr. Huttenhower:

Hear about the ongoing evolution of statistical tools in microbiome research and participate in a live Q&A session with Dr. Huttenhower.

Speaker

Curtis Huttenhower, Ph.D.

Professor of Computational Biology and Bioinformatics
Co-Director, Harvard Chan Microbiome in Public Health Center
Associate Member, Broad Institute of MIT and Harvard
Departments of Biostatistics and Immunology and Infectious Diseases
Harvard T.H. Chan School of Public Health

Curtis Huttenhower, PhD, is a Professor of Computational Biology and Bioinformatics in the Departments of Biostatistics and Immunology and Infectious Diseases at the Harvard T.H. Chan School of Public Health, where he co-directs the Harvard Chan Microbiome in Public Health Center. He is an Associate Member at the Broad Institute's Microbiome Program. His lab focuses on computational methods for functional analysis of microbial communities and molecular epidemiology of the human microbiome. This includes systems biology reconstructions integrating metagenomic, metatranscriptomic, and other microbial community 'omics, microbiome ecology in health and disease, and its potential as a diagnostic tool and point of therapeutic intervention

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MaAsLin 3 for Microbiome Statistics and Epidemiology

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