数据与复现单细胞与空间组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
SP

spatial-transcriptomics-agent

维护者 FreedomIntelligence · 最近更新 2026年4月1日

End-to-end spatial transcriptomics analysis: QC, deconvolution, domain detection.

OpenClawNanoClaw分析处理复现实验spatial-transcriptomics-agent🧠 bioos extended suitesingle-cell & spatial agentsend

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/spatial-transcriptomics-agent

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • 运行 STAgent to align histology images ,支持 expression matrices,perform 聚类/SVG detection,、 generate literature-backed spatial reports。
  • Analysis of Visium/Xenium 或 similar ST 数据集s。
  • Visual reasoning over spatial plots,H&E images,或 cluster maps。
  • Automatically generating Scanpy/Squidpy code ,用于 new ST workflows。
  • Hypothesis generation about spatial gene expression patterns。

原始文档

SKILL.md 摘录

Core Capabilities

  1. Dynamic code generation: Create/execute Python scripts for QC, clustering, SVG detection.
  2. Visual reasoning: Interpret spatial plots to identify tissue domains and cell neighborhoods.
  3. Literature retrieval: Pull references that contextualize findings.
  4. Report generation: Deliver publication-style writeups with plots and SVG tables.

Workflow

  1. Env setup: conda env create -f environment.yml && conda activate STAgent.
  2. Data prep: Supply expression_path (.h5ad/Spaceranger) + image_path (H&E/IF) and metadata.
  3. Task selection: Choose tasks such as cluster, find_svg, annotate_domains, or composite instructions; run python repo/src/main.py --data_path ... --task "...".
  4. Execute & interpret: Let STAgent generate scripts, run analyses, and interpret results with literature references.
  5. Package outputs: Save UMAP/spatial plots, SVG tables, QC details, and summary markdown.

Guardrails

  • Document coordinate systems and any scaling between imaging and expression coordinates.
  • Avoid definitive cell-type labels without supporting markers.
  • Capture QC parameters for reproducibility.

适用场景

  • Use spatial-transcriptomics-agent ,用于 single-cell 或 spatial omics analysis。
  • Apply spatial-transcriptomics-agent to 聚类,integration,或 trajectory workflows。

不适用场景

  • Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。

相关技能

相关技能

返回目录
AN
数据与复现单细胞与空间组学

AnnData

AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observ…

Claude CodeOpenClaw分析处理
K-Dense-AI/claude-scientific-skills查看
BI
数据与复现单细胞与空间组学

bio-imaging-mass-cytometry-cell-segmentation

Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for n…

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看
BI
数据与复现单细胞与空间组学

bio-read-qc-umi-processing

Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep…

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看
BI
数据与复现单细胞与空间组学

bio-single-cell-batch-integration

Integrate multiple scRNA-seq samples/batches using Harmony, scVI, Seurat anchors, and fastMNN. Remove technical variatio…

OpenClawNanoClaw分析处理
FreedomIntelligence/OpenClaw-Medical-Skills查看