bio-hi-c-analysis-loop-calling
Detect chromatin loops and point interactions from Hi-C data using cooltools, chromosight, and HiCCUPS-like methods. Identify CTCF-mediated loops and enhancer-promoter contacts. Use when detecting chromatin loops from Hi-C data.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-hi-c-analysis-loop-calling --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: bedtools 2.31+, cooler 0.9+, cooltools 0.6+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, pybedtools 0.9+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Chromatin Loop Calling **"Call chromatin loops from my Hi-C data"** → Detect point enrichments in contact matrices representing CTCF-mediated loops and enhancer-promoter interactions. - Python: `cooltools.dots()` or `chromosight detect --pattern=loops` Detect chromatin loops and point interactions from Hi-C data. ## Required Imports ```python import cooler import cooltools import numpy as np import pandas as pd import matplotlib.pyplot as plt import bioframe ``` ## Call Loops with cooltools (Dot Calling) ```python clr = cooler.Cooler('matrix.mcool::resolutions/10000') view_df = bioframe.make_viewframe(clr.chromsizes) # Compute expected values ex
- Version Compatibility
- Required Imports
- Call Loops with cooltools (Dot Calling)
- Using chromosight (CLI)
- Parse chromosight Output
- Using HiCExplorer hicDetectLoops
- Loop Statistics
- Filter Loops by Score
- Annotate Loops with Features
- Compare Loops Between Conditions
- Aggregate Peak Analysis (APA)
- Using cooltools pileup for APA
- Export Loops
- Loops at Promoter-Enhancer Pairs
Call loops with chromosight chromosight detect \ matrix.cool \ loops_output Call loops with HiCExplorer hicDetectLoops \
What does the bio-hi-c-analysis-loop-calling skill do?
Detect chromatin loops and point interactions from Hi-C data using cooltools, chromosight, and HiCCUPS-like methods. Identify CTCF-mediated loops and enhancer-promoter contacts. Use when detecting chromatin loops from Hi-C data.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-hi-c-analysis-loop-calling --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.