bio-atac-seq-co-accessibility
Infer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linking enhancer accessibility to promoter accessibility, identifying enhancer-gene pairs from chromatin alone (without paired RNA), running gene-regulatory inference combining ATAC + RNA, or comparing predicted regulatory contacts against Hi-C/Micro-C ground truth.
npx skills add BioTender-max/awesome-bio-agent-skills --skill co-accessibility --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: Cicero 1.20+, monocle3 1.3+, ArchR 1.0.2+, SCENIC+ 1.0+, pycisTopic 1.0+, Signac 1.13+, GenomicRanges 1.54+, GenomicInteractions 1.36+, BSgenome.Hsapiens.UCSC.hg38 1.4+. Verify before use: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws unexpected errors, introspect the installed package and adapt rather than retrying. # Co-accessibility (cis-Regulatory Linkage) **"Which enhancers connect to which promoters in my scATAC data?"** -> Use cell-to-cell variability in joint accessibility of nearby peaks to infer cis-regulatory connections without explicit RNA expression. Output is a peak-pair graph with co-accessibility scores; thresholding produces enhancer-gene candidate pairs. - R: `cicero::run_cicero(input_cds, genomic_coords)` -> peak-pair connection scores - R: `ArchR::addCoAccessibility(proj)` -> ArchR-internal Cicero wrapper - Python: `pycisTopic` + `SCENIC+` for network-level inference combining ATAC + RNA + motifs Co-accessibility is NOT 3D contact; it's a statistical association based on cell-to-cell
- Version Compatibility
- What Co-accessibility Captures vs What It Doesn't
- Algorithmic Taxonomy
- How Cicero Works (Conceptually)
- Per-Tool Failure Modes
- Cicero -- alpha tuning shifts results
- Cicero -- metacell aggregation hides cell-type-specific connections
- Cicero -- distance assumption
- SCENIC+ -- RNA scaling
- LinkPeaks (Signac) -- Distance default
- Decision Tree by Goal
- Cicero Standard Workflow
- ArchR getCoAccessibility
- Visualizing Connections
What does the bio-atac-seq-co-accessibility skill do?
Infer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linking enhancer accessibility to promoter accessibility, identifying enhancer-gene pairs from chromatin alone (without paired RNA), running gene-regulatory inference combining ATAC + RNA, or comparing predicted regulatory contacts against Hi-C/Micro-C ground truth.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill co-accessibility --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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.