Load when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama.
$ npx skills add TianGzlab/OmicsClaw --skill spatial-integrate -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install TianGzlab/OmicsClaw spatial-integrate --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/spatial/spatial-integrate .claude/skills/spatial-integrate && 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 "spatial-integrate" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-integrate into .claude/skills/spatial-integrate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-integrate", 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/spatial/spatial-integrateType 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 spatial-integrate -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install TianGzlab/OmicsClaw spatial-integrate --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/spatial/spatial-integrate .agents/skills/spatial-integrate && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "spatial-integrate" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-integrate into .agents/skills/spatial-integrate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-integrate", 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 spatial-integrate -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install TianGzlab/OmicsClaw spatial-integrate --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/spatial/spatial-integrate .cursor/skills/spatial-integrate && 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 "spatial-integrate" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-integrate into .cursor/skills/spatial-integrate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-integrate", 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/spatial/spatial-integrate--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 spatial-integrate -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install TianGzlab/OmicsClaw spatial-integrate --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/spatial/spatial-integrate .gemini/skills/spatial-integrate && 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 "spatial-integrate" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-integrate into .gemini/skills/spatial-integrate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-integrate", 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 spatial-integrateInstalls 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 spatial-integrate -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/spatial/spatial-integrate .github/skills/spatial-integrate && 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 "spatial-integrate" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-integrate into .github/skills/spatial-integrate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-integrate", 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 spatial-integrate -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 spatial-integrate --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/spatial/spatial-integrate .opencode/skills/spatial-integrate && 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 "spatial-integrate" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-integrate into .opencode/skills/spatial-integrate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-integrate", 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.
spatial-integrateLoad when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama.
Spatial Integrate is an agent skill from TianGzlab/OmicsClaw. Load when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama. Skip physical coordinate alignment (use spatial-register) and single-batch data (use spatial-domains).
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including reference files (for example `_api.py`, `examples/example_step.py` and `r_visualization/README.md`).
It sits in AI & LLM Engineering. It works with AnnData and UMAP. 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 and R), 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.
Spatial Integrate loads about 1.3k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 58 tokens; SKILL.md has 464 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). 464 words, ~1,277 tokens.
.claude/skills/spatial-integrate/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.from skills._sdk.notebook import load_skill, read_input, write_output
library = load_skill("spatial-integrate")
adata = read_input("data/multi_sample.h5ad")
adata = library.integrate(adata, batch_key="sample")
write_output(adata, "intermediate/integrated.h5ad")Correct expression-space batch effects after spatial-preprocess. Harmony and Scanorama add corrected PCA-based embeddings; BBKNN replaces the neighbor graph. None aligns tissue coordinates or changes the expression matrix.
Input: preprocessed AnnData with obsm["X_pca"] and at least two labels in
obs["batch"] (or the chosen batch_key). Functions return AnnData, tables and
figures without writing files; see API below.
CLI writes processed.h5ad, report.md, result.json, batch-size and
integration tables, and the comparison gallery. The complete file inventory
and generation conditions are in references/output_contract.md.
Harmony adds X_pca_harmony; Scanorama adds X_scanorama;
BBKNN changes obsp["distances"] and obsp["connectivities"].
python skills/spatial/spatial-integrate/spatial_integrate.py \
--input multi_sample.h5ad --output results/integration --method harmony --batch-key sample
python skills/spatial/spatial-integrate/spatial_integrate.py --demo --output /tmp/spatial_integrateUse examples/example_step.py for load_skill, saved objects and replay.
references/parameters.md lists the CLI method flags.
X_pca must exist before integration; no normalization is performed here.X_scanorama is a corrected PCA-based embedding, not corrected gene expression.batch_entropy_after measures local mixing, not biological preservation;
inspect condition and cell-type structure before choosing a correction.run_info(adata, keep=False) removes only library diagnostics. The CLI keeps
its existing uns["spatial_integration"] summary.X_umap_before_integration and X_umap_after_integration preserve both views.<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->integrate(adata, *, method: str='harmony', batch_key: str='batch', random_state: int=0, **parameters)Integrate a multi-batch PCA representation in place, preserving expression.
:param adata: Preprocessed AnnData with X_pca and batch labels. :param method: harmony (default), bbknn (graph only), or scanorama. :param batch_key: Batch column in obs, default batch. :param random_state: Seed for Harmony, neighbors, UMAP and Leiden, default 0. BBKNN's default Annoy backend and Scanorama expose no seed here; their matching can vary across backend versions. :param parameters: Method keywords with original CLI defaults: Harmony theta=2, lamb=1, max_iter_harmony=10; BBKNN neighbors_within_batch=3, n_pcs=50, trim=None; Scanorama knn=20, sigma=15, alpha=0.1, batch_size=5000. :returns: The same AnnData with corrected embedding or graph, UMAP snapshots, per-spot batch entropy, and JSON run diagnostics. X is unchanged. :raises ValueError: Unknown method, missing batches/PCA, or invalid parameters. :raises ImportError: Missing backend; use install_skill_deps for that method.
run_info(adata, *, keep: bool=True) -> dictRead the last integration summary.
:param adata: AnnData returned by integrate. :param keep: True retains diagnostics; False removes them for CLI serialization. :returns: Summary including seed and effective method parameters, or an empty dict.
mixing_table(adata) -> pd.DataFrameReturn per-spot entropy before and after correction.
:param adata: Integrated AnnData. :returns: observation, batch_entropy_before, batch_entropy_after and batch_entropy_delta. :raises KeyError: Integration entropy columns are absent.
embedding_figure(adata, *, batch_key: str='batch')Compare the pre- and post-integration UMAP coordinates.
:param adata: Integrated AnnData with both UMAP snapshots. :param batch_key: Batch labels used for color, default batch. :returns: A matplotlib Figure; the caller saves and closes it. :raises KeyError: Batch labels or UMAP snapshots are absent.
<!-- api:end -->anndata, bbknn, harmonypy, matplotlib, numpy, pandas, scanorama, scanpy, scipy, seaborn
Missing method packages raise ImportError with an install_skill_deps hint.
© 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 10 other files (references) in skills/spatial/spatial-integrate of TianGzlab/OmicsClaw.
Open the folder on GitHubat commit 90a3bec
Spatial Integrate 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 |
|---|---|---|---|---|---|---|
| Spatial Integrate this skillTianGzlab/OmicsClaw | 161 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Alphagenome Predictionsgenomicsxai/alphagenome-pytorch | 162 | — | ~868 | Automated safety check: Pass | Apache-2.0 | |
| ScanpyK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~5.1k | Automated safety check: Pass | BSD-3-Clause | |
| Umap LearnK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~5.4k | Automated safety check: Pass | BSD-3-Clause | |
| Bio Flow Cytometry Clustering PhenotypingGPTomics/bioSkills | 1.2k | 1 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Bio Tcr Bcr Analysis Scirpy AnalysisGPTomics/bioSkills | 1.2k | 1 repos | ~4.4k | Automated safety check: Pass | MIT |
genomicsxai/alphagenome-pytorch
Run AlphaGenome-PyTorch to get genomic track predictions — via the agt predict CLI (single locus, BED regions, whole chromosomes, raw FASTA sequences, or per-gene count tables/AnnData), variant…
K-Dense-AI/scientific-agent-skills
Performs Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or…
K-Dense-AI/scientific-agent-skills
Applies UMAP-learn to nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.
GPTomics/bioSkills
Unsupervised clustering and cell-type identification for high-dimensional flow, spectral, and mass cytometry - FlowSOM, PhenoGraph, FlowSOM-via-CATALYST, with UMAP/tSNE for visualization.
GPTomics/bioSkills
Integrates single-cell paired TCR/BCR (10x VDJ, AIRR, dandelion, BD Rhapsody) with gene expression in an AnnData/MuData object using scirpy - chain-pairing QC, clonotype definition, clonal…
aipoch/medical-research-skills
Standard single-cell RNA-seq analysis pipeline. An agent skill from aipoch/medical-research-skills.
TianGzlab/OmicsClaw
Load when comparing gene expression between two conditions in bulk RNA-seq count data.
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 checking a bulk RNA-seq count matrix for library-size outliers, gene detection rates, and sample-sample correlation before DE.
TianGzlab/OmicsClaw
Load when checking raw single-cell FASTQ read quality (Phred / GC / adapter / length) before counting.
TianGzlab/OmicsClaw
Load when removing low-quality cells and lowly-detected genes from a single-cell AnnData using QC-derived thresholds or tissue presets.
TianGzlab/OmicsClaw
Load when ranking cluster-level marker genes from a clustered single-cell AnnData via Scanpy Wilcoxon / t-test / logreg or COSG specificity.
Categories
Load when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama. Spatial Integrate is an agent skill from TianGzlab/OmicsClaw. Load when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama.
Spatial Integrate fits situations like: AI & LLM Engineering work in your project.
Run `npx skills add TianGzlab/OmicsClaw --skill spatial-integrate -a claude-code`. Or copy the skill folder (skills/spatial/spatial-integrate in TianGzlab/OmicsClaw) into .claude/skills/spatial-integrate in your project. Claude Code loads it when a task matches its description.
Run `npx skills add TianGzlab/OmicsClaw --skill spatial-integrate -a codex`. Or copy the skill folder (skills/spatial/spatial-integrate in TianGzlab/OmicsClaw) into .agents/skills/spatial-integrate 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 spatial-integrate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spatial-integrate, .gemini/skills/spatial-integrate, .github/skills/spatial-integrate and .opencode/skills/spatial-integrate in your project.
Going by SKILL.md and its folder, Spatial Integrate needs Python and R 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.
Spatial Integrate 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 1.3k tokens (SKILL.md is roughly 5.1k 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 3.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Spatial Integrate: Alphagenome Predictions (genomicsxai/alphagenome-pytorch, 162 stars), Scanpy (K-Dense-AI/scientific-agent-skills, 48k stars), Umap Learn (K-Dense-AI/scientific-agent-skills, 48k stars) and Bio Flow Cytometry Clustering Phenotyping (GPTomics/bioSkills, 1.2k 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.
