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Merge multiple single-sample scRNA-seq count matrices (from sc-count) into one downstream-ready AnnData with sample labels.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills- --skill sc-multi-countコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
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SOC 職業分類に基づく
SKILL.md を表示中
| name | sc-multi-count |
| description | Merge multiple single-sample scRNA-seq count matrices (from sc-count) into one downstream-ready AnnData with sample labels. |
| version | 0.1.0 |
| author | OmicsClaw |
| license | MIT |
| tags | ["singlecell","scrna","count","merge","multi-sample","aggregate"] |
| metadata | {"omicsclaw":{"domain":"singlecell","requires":{"bins":"[Truncated]","env":"[Truncated]","config":"[Truncated]"},"emoji":"🧬","homepage":"https://github.com/TianGzlab/OmicsClaw","os":["macos","linux"],"install":["[Truncated]"],"trigger_keywords":["merge count matrices","multi-sample count","aggregate samples","combine count outputs","cellranger aggr alternative"],"allowed_extra_flags":["--sample-id","--r-enhanced"],"legacy_aliases":["scrna-multi-count"],"saves_h5ad":true,"requires_preprocessed":false,"param_hints":{"merge":"[Truncated]"}}} |
You are SC Multi-Count, a specialized OmicsClaw agent for merging multiple single-sample scRNA-seq count matrices into one downstream-ready AnnData.
sc-count, labels each
cell with its sample of origin, and writes a standardized processed.h5ad.layers['counts'], input
contract, matrix contract) that downstream skills expect.obs['sample_id'] for downstream batch
correction or per-sample comparison.processed.h5ad with
layers['counts'] and OmicsClaw input-contract metadata.README.md, report.md, result.json,
and rerun commands.| Format | Extension | Required Fields / Structure | Example |
|---|---|---|---|
| Multiple H5AD | .h5ad | each from sc-count output | --input s1/processed.h5ad --input s2/processed.h5ad |
| Demo | n/a | --demo flag | built-in split of PBMC demo |
| Requirement | Where it should exist | Why it matters |
|---|---|---|
| Per-sample count H5AD | --input (repeated) | each must be a count-level AnnData |
| Sample labels | --sample-id or inferred |
needed for obs['sample_id'] |
layers['counts'], record OmicsClaw contracts.report.md, result.json, and reproducibility bundle.processed.h5ad.# Merge two sc-count outputs
oc run sc-multi-count \
--input sample1/processed.h5ad \
--input sample2/processed.h5ad \
--output merged/
# With explicit sample IDs
oc run sc-multi-count \
--input s1/processed.h5ad --sample-id Patient_A \
--input s2/processed.h5ad --sample-id Patient_B \
--output merged/
# Demo mode
python omicsclaw.py run sc-multi-count --demo --output /tmp/sc_multi_count_demo
processed.h5ad, prefix barcodes with sample ID.layers['counts'], adata.raw, and OmicsClaw contracts.Key parameters:
| Parameter | Default | Description |
|---|---|---|
--input | required | path to a processed.h5ad (repeat for each sample) |
--sample-id | inferred | explicit sample label (repeat, matching order of --input) |
figure_data/.figures/manifest.json.output_directory/
├── README.md
├── report.md
├── result.json
├── processed.h5ad
├── standardized_input.h5ad -> processed.h5ad
├── figures/
│ ├── barcode_rank.png
│ ├── count_distributions.png
│ ├── count_complexity_scatter.png
│ ├── sample_composition.png
│ └── manifest.json
├── tables/
│ ├── barcode_metrics.csv
│ └── per_sample_summary.csv
├── figure_data/
│ ├── manifest.json
│ ├── barcode_metrics.csv
│ └── per_sample_summary.csv
└── reproducibility/
├── analysis_notebook.ipynb
├── commands.sh
└── requirements.txt
sc-count (run once per sample to produce individual processed.h5ad files)sc-qc for quality assessment on the merged objectsc-qc or sc-preprocessing on the merged processed.h5ad.sc-batch-integration if samples have batch effects.Required:
scanpy, anndata, pandas, numpy, matplotlib| Flag | Type | Default | Description |
|---|---|---|---|
--input | path (repeatable) | — | Path to a processed.h5ad from sc-count; repeat once per sample (required unless --demo) |
--output | path | — | Output directory (required) |
--demo | flag | false | Run with built-in demo data (splits PBMC demo into two synthetic samples) |
--sample-id | str (repeatable) | inferred | Explicit sample label for the corresponding --input; repeat in the same order as --input |
--r-enhanced | flag | false | Accepted for CLI consistency; no R Enhanced plots are generated by this skill |
This skill has no R Enhanced plots. --r-enhanced is accepted for CLI consistency but produces no additional output. The skill's purpose is multi-sample merging, not visualization beyond the standard Python gallery.