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 classifying perturbed vs non-perturbed cells in a Perturb-seq / CRISPR-screen scRNA AnnData via the pertpy Mixscape workflow.
$ npx skills add TianGzlab/OmicsClaw --skill sc-perturb -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-perturb --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-perturb .claude/skills/sc-perturb && 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-perturb" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-perturb into .claude/skills/sc-perturb/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-perturb", 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-perturbType 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-perturb -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-perturb --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-perturb .agents/skills/sc-perturb && 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-perturb" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-perturb into .agents/skills/sc-perturb/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-perturb", 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-perturb -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-perturb --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-perturb .cursor/skills/sc-perturb && 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-perturb" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-perturb into .cursor/skills/sc-perturb/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-perturb", 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-perturb--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-perturb -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install TianGzlab/OmicsClaw sc-perturb --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-perturb .gemini/skills/sc-perturb && 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-perturb" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-perturb into .gemini/skills/sc-perturb/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-perturb", 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-perturbInstalls 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-perturb -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-perturb .github/skills/sc-perturb && 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-perturb" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-perturb into .github/skills/sc-perturb/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-perturb", 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-perturb -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-perturb --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-perturb .opencode/skills/sc-perturb && 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-perturb" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/singlecell/scrna/sc-perturb into .opencode/skills/sc-perturb/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sc-perturb", 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.
sc-perturbLoad when classifying perturbed vs non-perturbed cells in a Perturb-seq / CRISPR-screen scRNA AnnData via the pertpy Mixscape workflow.
Sc Perturb is an agent skill from TianGzlab/OmicsClaw. Load when classifying perturbed vs non-perturbed cells in a Perturb-seq / CRISPR-screen scRNA AnnData via the pertpy Mixscape workflow. Skip when guide labels are not yet attached to the expression object (use sc-perturb-prep); in-silico KO predictions on unperturbed data (use sc-in-silico-perturbation).
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 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.
Read from SKILL.md and the folder at commit 90a3bec. It shows what the files ask for, not the result of running them.
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.
Ships script files (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Sc Perturb loads about 1.2k tokens when it runs, and up to ~1.7k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 426 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.
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.
The full file from TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 426 words, ~1,158 tokens.
.claude/skills/sc-perturb/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.Classify observed Perturb-seq cells with pertpy Mixscape. Guide labels and a
non-targeting control group must already exist; otherwise use sc-perturb-prep.
This is not an in-silico knockout predictor.
python skills/singlecell/scrna/sc-perturb/sc_perturb.py --demo --seed 0 --output /tmp/sc_perturb_demo
python skills/singlecell/scrna/sc-perturb/sc_perturb.py --input prepared.h5ad --pert-key perturbation --control NT --split-by replicate --seed 0 --output results/perturbmixscape (--method mixscape) is the only method. Tune --n-neighbors,
--logfc-threshold, --pval-cutoff and --perturbation-type KO|OE explicitly.
Upstream: sc-perturb-prep, or an AnnData with verified screen labels. Validate
labels, supply/compute PCA, build perturbation signatures, then classify cells.
Both pertpy stages receive --seed (API random_state, default 0).
Downstream: sc-de or sc-enrichment after reviewing target-level calls.
Uses normalized expression. Count-like X is saved in layers['counts'] and
log-normalized. Existing X_pca is reused; otherwise PCA is computed before the
legacy normalization step. Prefer an upstream PCA on appropriate normalized
features for real screens. The API leaves its input unchanged.
Input: .h5ad with a perturbation column, control label and optional split key.
The CLI writes processed.h5ad, report.md, result.json,
reproducibility/commands.sh, tables/mixscape_cell_classes.csv,
tables/mixscape_class_counts.csv, tables/mixscape_global_class_counts.csv
and figures/mixscape_global_classes.png. Plot data and their manifest are in
figure_data/; R-enhanced figures are optional.
result.json → data.params.split_by records the CLI's resolved split key. A missing CLI split column warns and disables splitting; the API instead raises unless you pass split_by=None.tables/mixscape_global_class_counts.csv must contain biological signal before you interpret a run. Exit 0 alone does not establish an effect; the example asserts KO detection in both known-effect groups.tables/mixscape_cell_classes.csv preserves target-specific and global classes plus mixscape_class_p_ko (or _oe). Posterior probabilities are not experimental validation.n_neighbors affects the split_by=None path.<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->
mixscape(adata, *, pert_key='perturbation', control='NT', split_by='replicate', n_neighbors=20, logfc_threshold=0.25, pval_cutoff=0.05, perturbation_type='KO', random_state=0)Return an AnnData copy with Mixscape classes and posterior probabilities.
Uses normalized expression, preserving count-like X in layers['counts'] before log-normalization. split_by=None selects nearest-neighbour controls. Both pertpy stages receive random_state; a missing control or split column raises ValueError. Requires pertpy (validated with 1.0.3 and sklearn 1.7.2).
run_info(adata, *, keep: bool=True)Return method, seed and output columns; keep=False removes the run record.
class_counts(adata)Return class and n_cells columns for target-specific Mixscape labels.
global_class_counts(adata)Return global_class and n_cells columns for control, KO/OE and NP cells.
global_class_figure(adata)Return a Figure of global Mixscape cell counts without saving files.
<!-- api:end -->
anndata, matplotlib, numpy, pandas, pertpy, scanpy, scipy, scikit-learn, filelock
The Python 3.11 CPU example is verified with pertpy==1.0.3,
scikit-learn==1.7.2, anndata==0.11.4, statsmodels==0.14.6 and
filelock==4.0.12. statsmodels 0.15 removed a private import used by this pertpy
release. It also needs filelock
at import time but omits it from dependency metadata. Its dependencies include
JAX; use the separate extended environment. blitzgsea may need pip's isolated
source build, which the production wheels-only installer does not perform.
© 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
SKILL.md and 9 other files (references) in skills/singlecell/scrna/sc-perturb of TianGzlab/OmicsClaw.
Open the folder on GitHubat commit 90a3bec
Sc Perturb 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 Perturb this skillTianGzlab/OmicsClaw | 161 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Scanpy Single-Cell Analysisdavila7/claude-code-templates | 32k | 15 repos | ~2.8k | Automated safety check: Pass | MIT | |
| ScgptJimLiu/science-skills | 227 | 4 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| PyDESeq2 Differential Expressiondavila7/claude-code-templates | 32k | 11 repos | ~4k | Automated safety check: Pass | MIT | |
| Anndatadavila7/claude-code-templates | 32k | 11 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Single-Cell Initial AnalysisLigphiDonk/Oh-my--paper | 738 | 1 repos | ~1.4k | Automated safety check: Pass | MIT |
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.
JimLiu/science-skills
Embed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology.
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.
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…
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.
harrisongzhang/TheVirtualBiotech
Single-cell RNA-seq data preparation and quality control pipeline.
TianGzlab/OmicsClaw
Load when the user needs Deterministic fixed-period 24-hour single-component cosinor OLS rhythm analysis for a bulk RNA time-course CSV.
TianGzlab/OmicsClaw
Load when correcting batch effects in bulk expression using R sva ComBat or the legacy Python parametric approximation.
TianGzlab/OmicsClaw
Load when discovering bulk gene co-expression modules and hub genes with R WGCNA.
TianGzlab/OmicsClaw
Load when comparing gene expression between two conditions in bulk RNA-seq count data.
TianGzlab/OmicsClaw
Load when estimating cell-type proportions in bulk RNA-seq samples from a single-cell or signature-matrix reference.
TianGzlab/OmicsClaw
Load when running pathway / GO term enrichment on a bulk RNA-seq DE result list.
Works with
Categories
Load when classifying perturbed vs non-perturbed cells in a Perturb-seq / CRISPR-screen scRNA AnnData via the pertpy Mixscape workflow. Sc Perturb is an agent skill from TianGzlab/OmicsClaw. Load when classifying perturbed vs non-perturbed cells in a Perturb-seq / CRISPR-screen scRNA AnnData via the pertpy Mixscape workflow.
Sc Perturb fits situations like: tasks that involve Bioinformatics.
Run `npx skills add TianGzlab/OmicsClaw --skill sc-perturb -a claude-code`. Or copy the skill folder (skills/singlecell/scrna/sc-perturb in TianGzlab/OmicsClaw) into .claude/skills/sc-perturb in your project. Claude Code loads it when a task matches its description.
Run `npx skills add TianGzlab/OmicsClaw --skill sc-perturb -a codex`. Or copy the skill folder (skills/singlecell/scrna/sc-perturb in TianGzlab/OmicsClaw) into .agents/skills/sc-perturb in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TianGzlab/OmicsClaw --skill sc-perturb -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-perturb, .gemini/skills/sc-perturb, .github/skills/sc-perturb and .opencode/skills/sc-perturb in your project.
Going by SKILL.md and its folder, Sc Perturb needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
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.
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.
Sc Perturb 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.
About 1.2k tokens (SKILL.md is roughly 4.6k 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 582 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Sc Perturb: Scanpy Single-Cell Analysis (davila7/claude-code-templates, 32k stars), Scgpt (JimLiu/science-skills, 227 stars), PyDESeq2 Differential Expression (davila7/claude-code-templates, 32k stars) and Anndata (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.