Workshop Information

This session will introduce several case studies featuring both targeted and untargeted metabolomics data. Through lectures on key concepts and analysis workflows, participants will learn data preprocessing and quality control using real LC-MS and NMR datasets. Additionally, they will explore case-control metabolomics studies through the application of statistical methods.

This session will cover bulk and single-cell RNA-seq analyses. It will cover experimental design, quality control, read mapping, differential expression analyses, as well as pathway and enrichment analyses. The single-cell RNA-seq part will also cover methods for unsupervised clustering and detection of subpopulations of cells.

This session will cover ChIP-seq and ATAC-seq analyses, which is commonly used for epigenomic analysis. It will cover experimental design, quality control, read mapping, identification of peaks, differential binding assays, and motif identification. Lectures will additionally cover theoretical aspects of peak identification as well as survey a number of commonly employed programs.

In this session, we will introduce the basic concepts and general ideas in constructing gene regulatory networks (GRNs), and focus on genomics studies for integrative analysis of transcriptomic and genomic data. With a case study in cancer research, we will go through cis-eQTL analysis and a state-of-the-art parallel algorithm 2SPLS to construct genome-wide GRNs. In addition, lectures will cover exploring the results by popular bioinformatics tools including STRING and Ingenuity Pathway Analysis.