AN
数据与复现
AnnData
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observ…
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数据与复现
RN
rna-velocity-agent
维护者 FreedomIntelligence · 最近更新 2026年4月1日
RNA velocity analysis with scVelo for trajectory and fate decision inference.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/rna-velocity-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
核心说明
- RNA Velocity Agent analyzes RNA velocity ，面向 single-cell RNA sequencing to predict cellular state transitions，differentiation trajectories，、 dynamic transcriptional regulation. It implements velocyto，scVelo，、 深度学习 approaches ，用于 trajectory inference。
- When inferring cell fate decisions 、 differentiation trajectories ，面向 scRNA-seq。
- To identify driver genes of cellular transitions。
- 用于 predicting future cell states ，面向 current transcriptional profiles。
- When analyzing developmental processes 或 disease progression dynamics。
原始文档
SKILL.md 摘录
Core Capabilities
-
Splicing-Based Velocity: Calculate RNA velocity from spliced/unspliced transcript ratios.
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Dynamic Modeling: Deep learning models (scVelo dynamical mode) for accurate velocity estimation.
-
Trajectory Inference: Project velocity vectors onto UMAP/PCA for differentiation flow visualization.
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Driver Gene Identification: Identify genes driving cell state transitions.
-
Latent Time Estimation: Reconstruct cellular pseudotime from velocity fields.
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Multi-Modal Velocity: Integrate protein (CITE-seq) or chromatin (ATAC) velocity.
Workflow
-
Input: scRNA-seq data with spliced/unspliced counts (from STARsolo, velocyto, kallisto-bustools).
-
Quality Control: Filter genes by splice detection rates and expression levels.
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Velocity Computation: Calculate velocity using steady-state or dynamical models.
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Embedding Projection: Project velocity onto low-dimensional representations.
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Trajectory Analysis: Identify root cells, terminal states, and differentiation paths.
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Driver Analysis: Rank genes by velocity-based contribution to transitions.
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Output: Velocity vectors, trajectory plots, driver genes, latent time estimates.
Example Usage
User: "Analyze RNA velocity in this hematopoiesis scRNA-seq dataset to map differentiation trajectories."
Agent Action:
适用场景
- When inferring cell fate decisions 、 differentiation trajectories ，面向 scRNA-seq。
- To identify driver genes of cellular transitions。
- 用于 predicting future cell states ，面向 current transcriptional profiles。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
上游相关技能
- Single_Cell - For general scRNA-seq analysis
- Single_Cell_Foundation_Models - For cell annotation
- Spatial_Transcriptomics - For spatial velocity
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