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 AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-rnaseq-quantgit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-SkillsWrote 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/alterlab-ieu/alterlab-academic-skills/alterlab-rnaseq-quant)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-rnaseq-quant"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-rnaseq-quant/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/alterlab-ieu/alterlab-academic-skills/alterlab-rnaseq-quant"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-rnaseq-quant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00214 | $0.03553 |
| Opus 5 | $0.00107 | $0.01776 |
| Sonnet 5 | $0.00043 | $0.00711 |
| Haiku 4.5 | $0.00021 | $0.00355 |
Grade A, and why
alterlab-rnaseq-quant 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RNA-seq Quantification — salmon & kallisto Transcript Abundance
The command-line quantification entry point for bulk RNA-seq: take raw FASTQ
reads plus a reference transcriptome and produce transcript-level abundance
estimates (counts + TPM) with salmon (selective alignment) or kallisto
(pseudoalignment via kb-python), then aggregate to the gene level with
tximport/tximeta and hand off to alterlab-pydeseq2 for differential
expression. It is the raw-data-to-count-matrix pipeline that the repo's Python
analysis skills assume already ran.
Quick Start
Quantify these RNA-seq FASTQs with salmon and a decoy-aware index
Build a salmon gentrome index from this transcriptome + genome
Run kallisto / kb count on my paired-end reads
Turn my salmon quant.sf files into a gene-level count matrix for DESeq2
→ Build a decoy-aware index once, run salmon quant (or kb count) per
sample, then run scripts/build_tx2gene.py + scripts/import_quant.py to make
the tximport gene matrix and route it to alterlab-pydeseq2.
When to Use This Skill
Use this skill when the request is about getting from FASTQ to transcript or gene abundance with a lightweight quantifier:
- "Quantify my RNA-seq with salmon / kallisto."
- "Build a decoy-aware salmon index (gentrome + decoys.txt)."
- "Run selective alignment with
--validateMappings --gcBias." - "I have
quant.sffiles — make me a gene-level count matrix for DESeq2." - "Set up
tximport/tximetawith a tx2gene map." - "Use kb-python /
kb countto pseudoalign these reads."
Does NOT Trigger — route these to the right sibling
| The request is really about… | Route to |
|---|---|
| Differential expression on a count matrix (DESeq2 Wald tests, FDR, volcano) | alterlab-pydeseq2 |
Single-cell RNA-seq quantification (was salmon alevin) |
piscem + alevin-fry — see references/single_cell_alevin.md; downstream → alterlab-scanpy / alterlab-scvi-tools |
| FASTQ-to-VCF germline/somatic variant calling | alterlab-nf-core-sarek |
| 16S/ITS amplicon (microbiome) FASTQ-to-feature-table | alterlab-qiime2-amplicon |
| Spatial transcriptomics (Visium/Xenium) neighborhood analysis | alterlab-squidpy-spatial |
| Loading/manipulating the resulting matrix as an AnnData object | alterlab-anndata |
| BLAST/DIAMOND sequence similarity search | alterlab-blast |
| Quick gene/transcript ID lookups & reference fetch (Ensembl/RefSeq) | alterlab-gget |
| Aligned BAM manipulation, coverage, read counting from alignments | alterlab-pysam |
What ships with it
10 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.
- evals/evals.json 5.5 KB
- references/decoy_index.md 2.3 KB
- references/kallisto_kb.md 2.4 KB
- references/salmon_quant.md 2.5 KB
- references/single_cell_alevin.md 1.7 KB
- references/tool_versions.md 2.9 KB
- references/tximport_handoff.md 3.5 KB
- scripts/build_tx2gene.py 4.2 KB runs code
- scripts/import_quant.py 9.3 KB runs code
- scripts/make_decoys.py 4.6 KB runs code
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.
- 11d ago First seen · 271 lines · 214 tokens per session scan A 765f40d3631e
alterlab-rnaseq-quant is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 6d ago), licensed MIT. It adds 214 tokens to every session and 3,553 once invoked, about $0.0011 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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