Course objectives: underlying the diverse "-omics" technologies, there is a set of
stable patterns and core concepts for omics data analysis. After taking the course, you will
Develop a good knowledge of the concepts and approaches for omics data analysis;
Understand the subtleties or uniqueness of common omics data analysis workflows and key parameters;
Perform effective omics data analysis using our user-friendly omics tools (community or pro) through web interface
Target audience: senior undergraduates, graduate students, postdoctoral fellows, researchers and PIs who are interested in omics data analysis
Prerequisites: good understanding of molecular biology and basic statistics.
Course delivery: virtual via Zoom. We will share the Zoom link three days before each topic. All slides and lecture recordings will be available
in your home directory
Course content: for each topic, we will cover three components: core concepts, key tools, live demo & hands-on practices.
After an overview of key omics technologies and common patterns in omics data analysis (foundational lectures [2]),
we will start with transcriptomics [2], followed by gene regulatory networks and proteomics [2], metabolomics
[2], microbiomics [2], and finally, multi-omics integration [2]. In addition, we will also offer special
topics based on user feedback.