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single-cell-atlas

single-cell-atlas is a skill for Claude Code, Codex from zamushwani/biomedical-ai-skills. It costs 0 tokens per session (10,558 once invoked), scanned A, original, MIT.

A workflow for analysing single-cell RNA sequencing data, which measures gene activity in individual cells. It supports R and Python tools for cleaning data, grouping cells, identifying cell types, and studying their differences and relationships.

In plain words
What is it for?
Use it to process 10x Genomics data, remove poor-quality cells and doublets, find cell types, compare conditions, and create UMAP plots. It also supports trajectory, cell communication, and gene-regulation analyses.
Why use it?
It brings the many steps from raw cell counts to biological findings into one workflow. It also helps compare samples and experiments while accounting for technical differences between them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 1repo 1mo ago A scan 0 tokens original MIT

Good fit Use it to process 10x Genomics data, remove poor-quality cells and doublets, find cell types, compare conditions, and create UMAP plots. It also supports trajectory, cell communication, and gene-regulation analyses.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zamushwani/biomedical-ai-skills/single-cell-atlas
View source ↗ zamushwani/biomedical-ai-skills
Install

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.

Any agent
npx skills add zamushwani/biomedical-ai-skills --skill single-cell-atlas
Clone the repo
git clone --depth 1 https://github.com/zamushwani/biomedical-ai-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for single-cell-atlas

README.md
[![agentmods](https://agentmods.dev/badge/skills/zamushwani/biomedical-ai-skills/single-cell-atlas/github.svg)](https://agentmods.dev/skills/zamushwani/biomedical-ai-skills/single-cell-atlas)
Your own site
<a href="https://agentmods.dev/skills/zamushwani/biomedical-ai-skills/single-cell-atlas"><img src="https://agentmods.dev/badge/skills/zamushwani/biomedical-ai-skills/single-cell-atlas/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.

agentmods 80×15 button for single-cell-atlas

Your own site · 80×15
<a href="https://agentmods.dev/skills/zamushwani/biomedical-ai-skills/single-cell-atlas"><img src="https://agentmods.dev/badge/skills/zamushwani/biomedical-ai-skills/single-cell-atlas.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 10,558 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.10558
Opus 5.5 $0.00000 $0.04223
Sonnet 5.5 $0.00000 $0.02112
Haiku 4.5 $0.00000 $0.01056

Measured 2mo ago against content hash 17d968ae3c39, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

single-cell-atlas 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 2mo ago.

The scan reads SKILL.md. This mod also ships 4 executable files (tests/run_all.py, tests/validate_clustering.py, tests/validate_integration.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/single-cell-atlas/SKILL.md · 1,141 lines

How it starts

The opening of the file, as written. The whole thing — 1,141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Single-Cell Atlas Construction

Full single-cell RNA-seq pipeline from raw counts to biological interpretation. Covers QC, normalization, batch integration, clustering, annotation, pseudobulk DE, trajectory inference, cell-cell communication, and TF activity. Dual-language: Seurat v5 (R) and scanpy (Python).

When to Use This Skill

Activate when the user requests:

  • Single-cell RNA-seq quality control and preprocessing
  • 10x Chromium data processing (Cell Ranger output)
  • Doublet detection and removal
  • Normalization of UMI count matrices
  • Feature selection for dimensionality reduction
  • Processing scRNA-seq data before integration, clustering, or annotation
  • Batch integration across samples or experiments
  • Clustering and resolution selection
  • Automated or marker-based cell type annotation
  • UMAP visualization
  • Differential expression between conditions (pseudobulk)
  • Trajectory inference and RNA velocity
  • Cell-cell communication analysis
  • Transcription factor activity and gene regulatory networks

Inputs

Data Type Format Source
Count matrix 10x HDF5 (.h5), MEX (matrix.mtx + barcodes + features) Cell Ranger, STARsolo
Count matrix AnnData (.h5ad) for scanpy, Seurat object (.rds) for R Processed datasets
Reference PBMC 3k, Tabula Muris, HCA datasets 10x Genomics, HCA

Loading Data

Seurat v5 (R)

library(Seurat)  # v5.4+

# From Cell Ranger output (filtered_feature_bc_matrix/)
obj <- Read10X("path/to/filtered_feature_bc_matrix/") |>
  CreateSeuratObject(project = "sample1", min.cells = 3, min.features = 200)

# From HDF5
obj <- Read10X_h5("path/to/filtered_feature_bc_matrix.h5") |>
  CreateSeuratObject(project = "sample1", min.cells = 3, min.features = 200)

# Seurat v5 uses Assay5 (layers: counts, data, scale.data)
# Access counts: obj[["RNA"]]$counts or LayerData(obj, layer = "counts")

scanpy (Python)

import scanpy as sc  # v1.12+

# From Cell Ranger output
adata = sc.read_10x_mtx("path/to/filtered_feature_bc_matrix/", var_names="gene_symbols")

# From HDF5
adata = sc.read_10x_h5("path/to/filtered_feature_bc_matrix.h5")

# Store raw counts for later
adata.raw = adata.copy()

Read the full file on GitHub · 1,141 lines

Files

What ships with it

6 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.

Changes

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.

  1. 2mo ago First seen · 1,141 lines · 0 tokens per session scan A 17d968ae3c39

Subscribe to this mod's changes

single-cell-atlas is a skill published in the GitHub repository zamushwani/biomedical-ai-skills (1 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 10,558 tokens. 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 2026-08-31.

DESeq2Data and AIScientificai-agentai-skillsbioinformaticscancer-genomicscancer-research
Related

single-cell-atlas compared with skills from other repositories

single-cell-atlas next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
single-cell-atlaszamushwani/biomedical-ai-skillsSkill11mo agoMITA0Claude Code, Codex
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gene-protein-expression-matrix-normalizationaipoch/medical-research-skillsSkill2.0k1mo agoMITA63Claude Code, Codex
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torch-geometricK-Dense-AI/scientific-agent-skillsSkill56k5d agoMITA71Claude Code, Codex
bidsK-Dense-AI/scientific-agent-skillsSkill56k5d agoMITA84Claude Code, Codex