Bioinformatics for the 3D Genome: An Introduction to Analyzing and Interpreting Hi-C Data

Hi-C has transformed our understanding of 3D genome architecture, revealing how structural changes influence gene regulation and disease mechanisms. Yet, the rich data landscape Hi-C unlocks can seem intimidating - where do you even begin with Hi-C data analysis? If Hi-C bioinformatics feels like a black box, this webinar is for you!
In this one-hour webinar, 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.

[@jiachenlu1064]

Very elaborate explanation of the data analysis pipeline in a very soothing voice, I don't feel it's a task to watch, but also an enjoyment. This is the best video I found so far on HiC data.

[@riturajwizzard]

Wonderful presentation, very informative and helpful.

[@BFS4321]

Fantastic presentation!!!

[@user-ps2ec8yf7p]

Hi! I am a current UC Berkeley undergraduate student who is interested in doing plant computational biology research. I am now having trouble with the coding process of generating Hi-C data graph. Could you please share a video that briefly covers the coding aspect of Hi-C analysis and data representation? That will be much appreciated!

[@arimagenomics]

Hello, we just published a genome assembly bioinformatics video that you might find interesting, enjoy! ua-cam.com/video/MDpkF5ixQ8I/v-deo.html

[@smoreno5591]

It was great! I'm very interested in looking at code

[@xiaofuwei7302]

For my samples, we can only run once for low input (patient), if shallow sequencing doesn't give enough long range and have high pcr duplication results. There is no ways to save samples right?