Advanced Analytic Methods for Multi-omics Data Analysis and Integration

Catalog description

This course focuses on the analysis of high-dimensional omics data (including but are not restricted to transcriptomics, epigenomics, proteomics, metabolomics and microbiome data) generated through advanced high-throughput and massspectrum technologies in biomedical settings. The course will cover multi-omics experimental study designs, multivariate dimension reduction, multi-omics data analysis and multi-omics data integration techniques. We will introduce classic multivariate statistical methods including principal component analysis, projection to latent structures, canonical correlation analysis, factorization, feature selection and network analysis, as well as some recently developed statistical, machine learning, and AI methods. This course will use the free software R to perform all analysis.