An Introduction to Analyzing and Interpreting Hi-C Data
If Hi-C bioinformatics feels like a black box, this course is for you. In this short introductory course, hear from an expert Hi-C bioinformatician as we demystify Hi-C data analysis. Take a journey through data processing, downstream analysis, visualization and interpretation.
Learn about Hi-C alignment, filtering, binning, normalization, data visualization and interpretation.
Course Overview
What You Will Learn
- Hi-C method: A quick introduction to the Hi-C method and how it is used in human disease research.
- Pipeline overview: An overview of a typical bioinformatics pipeline for genome-wide Hi-C data.
- Alignment, filtering, binning, normalization — we’ll talk through what happens at each step and what you should pay attention to.
- Data visualization and interpretation: Interpreting the Hi-C contact matrix and heatmap, as well as identifying compartments, TADs, and loops.
- Tool selection: There are so many tools out there. Which do you choose? We will round out the webinar with an overview of popular Hi-C tools and pipelines.
About the Instructor
Sofia Nomikou, PhD, is a computational biologist in the Workflow Development team at Arima Genomics. She is involved in data processing and algorithm development for Arima products. Sofia received her PhD from the New York University School of Medicine, New York, where she worked on developing computational approaches to uncover mechanisms of chromatin regulation and alterations in cancer.
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