Scanpy Single-Cell Analysis
davila7/claude-code-templates
Walks through single-cell RNA-seq analysis with Scanpy: loading .h5ad and 10X data, QC, normalization, PCA and UMAP, Leiden clustering, marker genes and cell type annotation.
Load when scoring drug sensitivity per cluster on an annotated scRNA AnnData via simple-correlation against drug-target signatures or via CaDRReS-Sc pretrained models (GDSC / PRISM).
Install Sc Drug Response
$ npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-drug-response --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/singlecell/scrna/sc-drug-response .claude/skills/sc-drug-response && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "sc-drug-response" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-response into .claude/skills/sc-drug-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-drug-response", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-responseType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-drug-response --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/singlecell/scrna/sc-drug-response .agents/skills/sc-drug-response && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sc-drug-response" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-response into .agents/skills/sc-drug-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-drug-response", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-drug-response --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/singlecell/scrna/sc-drug-response .cursor/skills/sc-drug-response && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sc-drug-response" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-response into .cursor/skills/sc-drug-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-drug-response", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/TianGzlab/OmicsClaw.git --path skills/singlecell/scrna/sc-drug-response--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-drug-response --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/singlecell/scrna/sc-drug-response .gemini/skills/sc-drug-response && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sc-drug-response" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-response into .gemini/skills/sc-drug-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-drug-response", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install TianGzlab/OmicsClaw sc-drug-responseInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/singlecell/scrna/sc-drug-response .github/skills/sc-drug-response && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sc-drug-response" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-response into .github/skills/sc-drug-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-drug-response", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-drug-response --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/singlecell/scrna/sc-drug-response .opencode/skills/sc-drug-response && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sc-drug-response" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-drug-response into .opencode/skills/sc-drug-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-drug-response", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sc-drug-response- GitHub stars
- 161
- Token cost
- ~1.3k tokens
- SKILL.md length
- 511 words
- Files
- 9 (incl. references)
- Skills in repo
- 88
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Load when scoring drug sensitivity per cluster on an annotated scRNA AnnData via simple-correlation against drug-target signatures or via CaDRReS-Sc pretrained models (GDSC / PRISM).
- Tasks that involve Bioinformatics
- SKILL.md covers Key CLI, Methods and Workflow, Inputs & Outputs and Gotchas, plus 2 more sections
- Runs Python scripts from its folder; calls python
What it does
Sc Drug Response is an agent skill from TianGzlab/OmicsClaw. Load when scoring drug sensitivity per cluster on an annotated scRNA AnnData via simple-correlation against drug-target signatures or via CaDRReS-Sc pretrained models (GDSC / PRISM). Skip when the AnnData has no cluster labels yet (use sc-clustering); predicting genetic-perturbation effects (use sc-in-silico-perturbation).
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `_api.py`, `examples/example_step.py` and `references/methodology.md`).
It sits in Research & Science, covering Bioinformatics. It works with AnnData. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Bioinformatics
Example prompts
- “/sc-drug-response”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 90a3bec. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Sc Drug Response loads about 1.3k tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 511 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 511 words, ~1,294 tokens.
Download SKILL.mdSave it as
.claude/skills/sc-drug-response/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- sc-drug-response
- description
- Load when scoring drug sensitivity per cluster on an annotated scRNA AnnData via simple-correlation against drug-target signatures or via CaDRReS-Sc pretrained models (GDSC / PRISM). Skip when the AnnData has no cluster labels yet (use sc-clustering); predicting genetic-perturbation effects (use sc-in-silico-perturbation).
- tags
- singlecell, scrna, drug-response, pharmacogenomics, cadrres, gdsc, prism
sc-drug-response
Summarize drug-associated gene expression or apply supplied CaDRReS models. The default does not predict drug sensitivity or recommend treatment.
Key CLI
python skills/singlecell/scrna/sc-drug-response/sc_drug_response.py --demo --output /tmp/sc_drug_demo
python skills/singlecell/scrna/sc-drug-response/sc_drug_response.py --input clustered.h5ad --cluster-key leiden --output results/drug_expression
python skills/singlecell/scrna/sc-drug-response/sc_drug_response.py --input clustered.h5ad --cluster-key leiden --method cadrres --drug-db gdsc --model-dir /path/to/trusted/models --output results/cadrresMethods and Workflow
simple_correlation is a legacy CLI name for mean expression, not correlation.
It averages available genes in each drug-associated gene set and cell group,
reports mean_target_expression, and ranks those descriptive means. Built-in
sets include targets, resistance and response-associated genes with no signed
weights. More expression does not imply more sensitivity or clinical benefit.
cadrres requires the omicverse adapter, a local CaDRReS-Sc checkout and trusted
pretrained model files. No models are bundled or downloaded. The old release
download links are unavailable; no replacement source is claimed here. Returned
Score is model output: inspect its units and direction, not just rank.
Upstream: sc-preprocessing and cluster/cell-type annotation. Downstream:
inspect gene overlap and expression patterns before any experimental follow-up.
Inputs & Outputs
Input: normalized expression in .h5ad with gene symbols and a group column.
PCA/neighbours are not required for scoring. The CLI writes processed.h5ad,
tables/drug_rankings.csv, report.md, result.json and
reproducibility/commands.sh. Bar/heatmap figures are written when scores are
available; figures/drug_sensitivity_umap.png is a legacy filename and requires
UMAP. obs['drug_score_<drug>'] are legacy names for the same group-level values,
not per-cell response predictions. Temporary CaDRReS CSV files are not public outputs.
Gotchas
tables/drug_rankings.csvhasmean_target_expressionfor the default andScorefor CaDRReS. Do not compare their units.result.json→summary.n_drugs_scoredis zero if no gene set overlaps; reviewTargetGenes,TotalTargetsandOverlapPctin the table.- Pass
--cluster-keyon real data; automatic selection can choose an unintended categorical column. The API acceptscluster_key=Noneto summarize all cells. --method cadrres --demogenerates explicitly synthetic plumbing scores without a real model. The API never substitutes synthetic predictions for a missing model.report.mdincludes the SDK's OmicsClaw research-use disclaimer unchanged.
API
<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->Show full SKILL.md (222 more words)Show less
score_drug_targets(adata, *, cluster_key=None, drug_targets=None)
Return mean_target_expression for each drug-associated gene set and group.
Averages X over available genes and cells, rounding to four decimals to preserve the CLI table. No model is fitted; this is neither correlation nor drug sensitivity, and high expression does not establish benefit. Pass normalized expression and a group key; None summarizes all cells together.
builtin_drug_targets()
Return a copy of 15 illustrative drug-associated gene sets.
These include targets, resistance and response-associated genes without direction or potency weights. They are not a validated response signature.
cadrres(adata, *, cluster_key, model_dir, drug_db='gdsc', n_drugs=10)
Return CaDRReS model scores using explicitly supplied trusted local models.
Requires omicverse's Drug_Response adapter and a CaDRReS-Sc checkout beside model_dir or under the home directory. Models are not bundled or downloaded; upstream download locations have not been validated. Temporary predictions do not modify model_dir. Score units and direction depend on the model.
run_info(table, *, keep: bool=True)
Return score interpretation; keep=False removes the table's run record.
top_drugs(table, *, n_top=10)
Return drug means across groups, ordered by decreasing descriptive/model score.
Ranking model scores this way preserves the CLI order, not clinical benefit.
top_drugs_figure(table, *, n_top=10)
Return a Figure labelled with expression or model-score units, without saving.
<!-- api:end -->Dependencies
anndata, matplotlib, numpy, omicverse, pandas, scanpy, scipy, seaborn
omicverse is needed only for the model-backed method. The default and notebook example use local expression means without CaDRReS.
© TianGzlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 8 other files (references) in skills/singlecell/scrna/sc-drug-response of TianGzlab/OmicsClaw.
- SKILL.md
- _api.py
- examples/example_step.py
- references/methodology.md
- references/output_contract.md
- references/parameters.md
- sc_drug_response.py
- tests/test_drug_api.py
- tests/test_sc_drug_response_methods.py
Open the folder on GitHubat commit 90a3bec
Compare with similar skills
Sc Drug Response next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sc Drug Response this skillTianGzlab/OmicsClaw | 161 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Scanpy Single-Cell Analysisdavila7/claude-code-templates | 33k | 15 repos | ~2.8k | Automated safety check: Pass | MIT | |
| ScgptJimLiu/science-skills | 228 | 4 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| PyDESeq2 Differential Expressiondavila7/claude-code-templates | 33k | 11 repos | ~4k | Automated safety check: Pass | MIT | |
| Anndatadavila7/claude-code-templates | 33k | 11 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Single-Cell Initial AnalysisLigphiDonk/Oh-my--paper | 739 | 1 repos | ~1.4k | Automated safety check: Pass | MIT |
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Scgpt
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Embed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology.
PyDESeq2 Differential Expression
davila7/claude-code-templates
Runs differential gene expression analysis on bulk RNA-seq counts with PyDESeq2: design formulas, Wald tests, FDR correction and volcano or MA plots.
Anndata
davila7/claude-code-templates
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling…
Single-Cell Initial Analysis
LigphiDonk/Oh-my--paper
Runs a seven-step quality-control and exploration pipeline on scRNA-seq, CyTOF or flow cytometry data and writes a plain-language report of what it found.
Single Cell Data Prep Qc
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Single-cell RNA-seq data preparation and quality control pipeline.
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Related
Works with
Categories
Questions about Sc Drug Response
What does Sc Drug Response do?
Load when scoring drug sensitivity per cluster on an annotated scRNA AnnData via simple-correlation against drug-target signatures or via CaDRReS-Sc pretrained models (GDSC / PRISM). Sc Drug Response is an agent skill from TianGzlab/OmicsClaw. Load when scoring drug sensitivity per cluster on an annotated scRNA AnnData via simple-correlation against drug-target signatures or via CaDRReS-Sc pretrained models (GDSC / PRISM).
When should I use Sc Drug Response?
Sc Drug Response fits situations like: tasks that involve Bioinformatics.
How do I install Sc Drug Response in Claude Code?
Run `npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a claude-code`. Or copy the skill folder (skills/singlecell/scrna/sc-drug-response in TianGzlab/OmicsClaw) into .claude/skills/sc-drug-response in your project. Claude Code loads it when a task matches its description.
How do I install Sc Drug Response in Codex?
Run `npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a codex`. Or copy the skill folder (skills/singlecell/scrna/sc-drug-response in TianGzlab/OmicsClaw) into .agents/skills/sc-drug-response in your project. Codex loads it when a task matches its description.
Can I use Sc Drug Response in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TianGzlab/OmicsClaw --skill sc-drug-response -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sc-drug-response, .gemini/skills/sc-drug-response, .github/skills/sc-drug-response and .opencode/skills/sc-drug-response in your project.
What does Sc Drug Response need to run?
Going by SKILL.md and its folder, Sc Drug Response needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Sc Drug Response access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Sc Drug Response safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Sc Drug Response use?
Sc Drug Response is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Sc Drug Response use?
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 529 tokens, read only when the agent opens those files.
What are the alternatives to Sc Drug Response?
Skills that share tags, products or a category with Sc Drug Response: Scanpy Single-Cell Analysis (davila7/claude-code-templates, 33k stars), Scgpt (JimLiu/science-skills, 228 stars), PyDESeq2 Differential Expression (davila7/claude-code-templates, 33k stars) and Anndata (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sc Drug Response?
TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 7, 2026.
Source: TianGzlab/OmicsClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.