Statistical and Computational Methods for Microbiome Data Analysis

This short course is motivated by the transformative impact the microbiome holds for human health. Understanding its role has the potential to revolutionize precision medicine. With vast amounts of microbiome data generated from sequencing techniques and curated in public databases, there is an urgent need for appropriate analysis to gain biological insights. The burgeoning field of microbiome data analysis has seen numerous method developments. This course will provide a comprehensive overview of statistical and computational methods for microbiome data analysis. It will cover data acquisition, processing, normalization, and visualization using state-of-the-art analytic pipelines. Detailed presentations explore statistical and computational methods for tasks like differential abundance analysis, regression, generative models, and network analysis. We will also discuss emerging research topics like longitudinal data analysis and data integration. Participants will gain a strong understanding of existing methods, future directions, and be able to perform basic microbiome data processing and analysis. The course emphasizes practical application by demonstrating the use of state-of-the-art software tools. By empowering participants to unlock the potential of microbiome data, this course aims to shape the future of microbiome research and its impact on human health.