https://github.com/bioinfomachinelearning/bml_hic_data_analysis

A set of tools for Hi-C data analysis developed by Bioinformatics and Machine Learning Lab
https://github.com/bioinfomachinelearning/bml_hic_data_analysis

Last synced: 2 months ago
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A set of tools for Hi-C data analysis developed by Bioinformatics and Machine Learning Lab

• Host: GitHub
• URL: https://github.com/bioinfomachinelearning/bml_hic_data_analysis
• Owner: BioinfoMachineLearning
• License: gpl-3.0
• Created: 2022-01-28T15:47:33.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2023-01-18T22:26:38.000Z (over 3 years ago)
• Last Synced: 2025-09-09T16:34:22.836Z (8 months ago)
• Language: Python
• Size: 66.4 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# BML_HiC_Data_Analysis

A set of tools for Hi-C data analysis developed by Bioinformatics and Machine Learning Lab

### TODO

- [x] Attached are the chromatin state bed files. We have 10 states for young and old (O_E1, O_E2, etc; O_E1 means chromatin state 1 in old MuSCs), there is genome location information in each file, could you calculate the contact frequency for each state?  I can put this Hic contact information on ChromHMM analysis.

- [ ] Could you give us some examples to show the visualization for enhancer-related differential loops on the genome browser and HiC maps? I already send some regions to you. I will have a presentation next Wednesday in our LGG meeting, if you can give this before Wednesday, that would be great.

- [ ] You can do some analysis to show what’s the difference with age at compartment, TAD, and loop levels.  I attached the pre-published paper here, you can look at Fig6.

- [ ] Files to visualize arcs in UCSC genome browser

- [ ] Some basic QC with the HiC data to include in Supplement

- [ ] PCA of compartments, TADs and loops