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bio-hi-c-analysis-loop-calling

Maintainer FreedomIntelligence · Last updated April 1, 2026

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.

OpenClawNanoClawAnalysisReproductionbio-hi-c-analysis-loop-calling🧬 bioinformatics (gptomics bio-* suite)bioinformatics — epigenomics & chromatindetect

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-hi-c-analysis-loop-calling

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

Python: cooltools.dots() or chromosight detect --pattern=loops.
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.
expected = cooltools.expected_cis(clr, view_df=view_df, ignore_diags=2).

Source Doc

Excerpt From SKILL.md

Call Loops with cooltools (Dot Calling)

clr = cooler.Cooler('matrix.mcool::resolutions/10000')
view_df = bioframe.make_viewframe(clr.chromsizes)

## Call dots (loops)

dots = cooltools.dots(
    clr,
    expected=expected,
    view_df=view_df,
    max_loci_separation=2000000,  # Max loop size (2Mb)
    max_nans_tolerated=0.5,
)

print(f'Found {len(dots)} loops')
print(dots.head())