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bio-single-cell-metabolite-communication

Analyze metabolite-mediated cell-cell communication from scRNA-seq data.

Updated Mar 30, 2026
Search Tags:#anndata#scRNA-seq#metabolite#cell-cell-communication#mebocost#permutations
One-click install
npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-single-cell-metabolite-communication
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-single-cell-metabolite-communication
Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/bio-single-cell-metabolite-communication
Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-single-cell-metabolite-communication

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze metabolite-mediated cell-cell communication from scRNA-seq data to reveal how different cell types influence each other's metabolism and signaling.

Core Features & Use Cases

  • Predict metabolite secretion from enzyme expression and identify sensing receptors.
  • Compute sender-receiver metabolite communication scores and highlight significant interactions.
  • Customize cell-type groupings and permutation-based significance testing for robust results.

Quick Start

Load your annotated scRNA-seq data, run MeboCost to infer metabolite-based communications, and review significant sender-receiver interactions.

Frequently Asked Questions about bio-single-cell-metabolite-communication

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I infer metabolite-mediated cell-cell communication from scRNA-seq data?▼

To infer metabolite-mediated cell-cell communication from scRNA-seq data, load your annotated scRNA-seq data and run MeboCost to predict metabolite secretion from enzyme expression and identify sensing receptors.

What is metabolite-based intercellular crosstalk and how is it calculated?▼

Metabolite-based intercellular crosstalk is calculated by predicting metabolite secretion from enzyme expression and identifying sensing receptors to compute sender-receiver communication scores across different cell types.

Does MeboCost require specific gene symbol annotations for scRNA-seq analysis?▼

Yes, MeboCost requires scRNA-seq data to include gene symbol annotations specifically for metabolic enzymes and receptors to successfully predict metabolite secretion and identify sensing interactions.

How do I test the significance of metabolite-receptor interactions in single-cell data?▼

To test the significance of metabolite-receptor interactions in single-cell data, apply permutation-based significance testing within MeboCost to validate robust sender-receiver metabolic crosstalk.

Can I customize cell-type groupings when analyzing metabolic signaling?▼

Yes, you can customize cell-type groupings when analyzing metabolic signaling to focus on specific intercellular metabolic crosstalk and metabolite-receptor interactions tailored to your tissue study.

What is the best way to study metabolite secretion and sensing receptors across tissues?▼

The best way to study metabolite secretion and sensing receptors across tissues is using MeboCost with scRNA-seq data to calculate communication scores and apply permutation-based significance testing for robust interactions.

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