Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add GPTomics/bioSkills --skill allele-specific-accessibilitygit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gptomics/bioskills/allele-specific-accessibility)<a href="https://agentmods.dev/skills/gptomics/bioskills/allele-specific-accessibility"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/allele-specific-accessibility/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gptomics/bioskills/allele-specific-accessibility"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/allele-specific-accessibility.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00093 | $0.04582 |
| Opus 5 | $0.00046 | $0.02291 |
| Sonnet 5 | $0.00019 | $0.00916 |
| Haiku 4.5 | $0.00009 | $0.00458 |
Grade A, and why
bio-atac-seq-allele-specific-accessibility scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-atac-seq-allele-specific-accessibility — 95% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: WASP 0.3.4+, GATK 4.4+, RASQUAL 1.1+, samtools 1.19+, bcftools 1.19+, vcftools 0.1.16+, plink 2.00+, MatrixEQTL 2.3+, QuASAR 0.1+, bowtie2 2.5+, bwa-mem2 2.2.1+, scipy 1.11+ (false_discovery_control), pandas 2+, pybedtools 0.10+.
Verify before use:
- CLI:
<tool> --versionthen<tool> --helpto confirm flags - Python:
pip show <package>thenhelp(module.function)to check signatures - R:
packageVersion('<pkg>')then?function_nameto verify parameters
If code throws unexpected errors, introspect the installed package and adapt rather than retrying.
Allele-Specific Accessibility
"Does this heterozygous SNP affect chromatin accessibility on its allele?" -> Count ATAC reads supporting reference vs alternative allele at heterozygous sites in the same individual; significant deviation from 50:50 indicates cis-regulatory effect. Requires careful handling of reference-allele mapping bias (WASP filtering) and within-individual binomial testing.
- CLI:
WASP(Geijn 2015) for de-biased reference mapping - CLI:
gatk ASEReadCounterfor allele-specific count tables - CLI:
RASQUAL(Kumasaka 2016) for joint cis-mapping with allelic counts - R:
QuASAR(Harvey 2015) for genotype + ASE inference simultaneously
ASE/ASB analysis is fundamentally different from cohort-level differential. Statistical framework is binomial within-individual; sample size is the count of heterozygous SNPs in accessible regions, not the number of individuals.
Algorithmic Taxonomy
| Tool | Method | Input | Strength | Fails when |
|---|---|---|---|---|
| WASP (Geijn 2015) | Realign reads where alt allele swap could change mapping; filter mapping-bias affected sites | BAM + VCF + reference | Mandatory for any ASE/ASB analysis; controls reference-allele bias | Slow on deep coverage; requires re-alignment step |
| GATK ASEReadCounter | Count REF and ALT reads at known heterozygous sites | BAM + VCF | Mature; integrates with GATK ecosystem; standard counter | Doesn't fix mapping bias (needs WASP first); single-sample |
| RASQUAL (Kumasaka 2016) | Joint cis-eQTL/caQTL model: total counts + allelic imbalance | BAM + VCF + peak counts | Best statistical power for caQTL when sample size is moderate (N=20-100); models genotype uncertainty | Complex setup; per-feature regression (slow); requires LD computation |
| QuASAR (Harvey 2015) | Genotype + ASE inference from RNA-seq or ATAC alone | BAM (no VCF needed) | Useful when genotypes are limited; integrates phasing | Less accurate than WASP+GATK when genotypes are known |
| MatrixEQTL on per-feature counts | Linear model fit on accessibility per peak | Genotypes + peak counts | Standard cohort-level caQTL; well-supported | No allelic imbalance information; needs sample size N >= 50 |
| Allelic Imbalance from Bayesian models (MAJIQ-style) | Bayesian beta-binomial | BAM + VCF | Models overdispersion appropriately | Niche; less mature than WASP+GATK |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 303 lines · 93 tokens per session scan A 516426242161
bio-atac-seq-allele-specific-accessibility is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 24d ago), licensed MIT. It adds 93 tokens to every session and 4,582 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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