{"id":44964469,"url":"https://github.com/bioinfomachinelearning/bml_hic_data_analysis","last_synced_at":"2026-02-18T14:09:26.862Z","repository":{"id":104968436,"uuid":"453124746","full_name":"BioinfoMachineLearning/BML_HiC_Data_Analysis","owner":"BioinfoMachineLearning","description":"A set of tools for Hi-C data analysis developed by Bioinformatics and Machine Learning Lab","archived":false,"fork":false,"pushed_at":"2023-01-18T22:26:38.000Z","size":68,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-09T16:34:22.836Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BioinfoMachineLearning.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2022-01-28T15:47:33.000Z","updated_at":"2024-09-05T14:47:39.000Z","dependencies_parsed_at":null,"dependency_job_id":"afcf3397-f07a-4b14-a298-b5b09563dcb1","html_url":"https://github.com/BioinfoMachineLearning/BML_HiC_Data_Analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/BioinfoMachineLearning/BML_HiC_Data_Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2FBML_HiC_Data_Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2FBML_HiC_Data_Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2FBML_HiC_Data_Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2FBML_HiC_Data_Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BioinfoMachineLearning","download_url":"https://codeload.github.com/BioinfoMachineLearning/BML_HiC_Data_Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2FBML_HiC_Data_Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29581620,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-18T13:56:48.962Z","status":"ssl_error","status_checked_at":"2026-02-18T13:54:34.145Z","response_time":162,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-02-18T14:09:26.056Z","updated_at":"2026-02-18T14:09:26.846Z","avatar_url":"https://github.com/BioinfoMachineLearning.png","language":"Python","readme":"# BML_HiC_Data_Analysis\nA set of tools for Hi-C data analysis developed by Bioinformatics and Machine Learning Lab\n\n\n### TODO\n- [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.\n- [ ] 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.\n- [ ] 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.\n- [ ] Files to visualize arcs in UCSC genome browser\n- [ ] Some basic QC with the HiC data to include in Supplement\n- [ ] PCA of compartments, TADs and loops","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbioinfomachinelearning%2Fbml_hic_data_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbioinfomachinelearning%2Fbml_hic_data_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbioinfomachinelearning%2Fbml_hic_data_analysis/lists"}