bio-hi-c-analysis-compartment-analysis
Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-hi-c-analysis-compartment-analysis --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: cooler 0.9+, cooltools 0.6+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scipy 1.12+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Compartment Analysis **"Identify A/B compartments from my Hi-C data"** → Decompose the contact matrix via eigenvector analysis to classify chromatin into active (A) and inactive (B) compartments. - Python: `cooltools.eigs_cis(clr, gc_cov)` for eigenvector decomposition Detect A/B compartments from Hi-C contact matrices. ## Required Imports ```python import cooler import cooltools import cooltools.lib.plotting import numpy as np import pandas as pd import matplotlib.pyplot as plt import bioframe ``` ## Compute Compartment Eigenvectors ```python clr = cooler.Cooler('matrix.mcool::resolutions/100000') # Get reference genome info view_df = bioframe.make_viewframe(clr.chromsizes) # Compute expected values first expected = cooltools.
- Version Compatibility
- Required Imports
- Compute Compartment Eigenvectors
- Use GC Content for Phasing
- Extract Compartment Calls
- Compartment Strength (Saddle Plot)
- Plot Saddle
- Compartment Strength Score
- Plot Eigenvector Track
- Export Compartment Calls
- Compare Compartments Between Samples
- Correlate with Gene Expression
- Related Skills
What does the bio-hi-c-analysis-compartment-analysis skill do?
Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-hi-c-analysis-compartment-analysis --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.