envi-pkg-local-improved

Consolidate ENVI documentation and tutorials for scRNA-seq and spatial data workflows.

1|Updated Dec 3, 2025

Search Tags:#documentation #tutorials #spatial-transcriptomics #scRNA-seq #covet #envi

Ready to run

npx skills add https://github.com/Ketomihine/my_skills --skill envi-pkg-local-improved

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: envi-pkg-local-improved
Source: https://github.com/Ketomihine/my_skills/tree/main/envi-pkg-local-improved
Command: npx skills add https://github.com/Ketomihine/my_skills --skill envi-pkg-local-improved

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill consolidates ENVI spatial transcriptomics documentation, tutorials, and Python sources to help researchers learn, implement, and extend ENVI workflows.

Core Features & Use Cases

Official documentation suite: Core concepts, installation guidance, API references, and tutorials for ENVI and COVET.
Practical workflows: Step-by-step MERFISH and scRNA-seq integration, latent embedding generation, imputation, and niche analysis.
Use case examples: End-to-end pipelines from data loading to visualization, including COVET-based niche computation and diffusion/UMAP analyses.

Quick Start

Clone the repository and start with the Getting Started guides in references/getting_started.md, then follow the tutorials to run ENVI end-to-end.

Frequently Asked Questions about envi-pkg-local-improved

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

FAQPage Schema

How do I integrate scRNA-seq data with spatial transcriptomics using ENVI?▼

ENVI integrates scRNA-seq data with spatial transcriptomics by leveraging documentation and tutorials that guide you through data loading, latent embedding generation, and imputation for joint spatial analysis.

What is COVET-based niche analysis and how does it work with spatial data?▼

COVET-based niche analysis is a spatial transcriptomics method supported by ENVI tutorials to compute cellular niches, generate joint embeddings, and perform downstream diffusion and UMAP visualizations.

How do I get started with ENVI spatial analysis workflows?▼

To get started with ENVI spatial analysis, clone the repository and follow the Getting Started guides in the references directory, then proceed to the step-by-step tutorials for end-to-end pipeline execution.

Can I use ENVI to visualize joint embeddings from MERFISH and scRNA-seq data?▼

Yes, ENVI supports visualizing joint embeddings from MERFISH and scRNA-seq data by providing practical workflows and tutorials that cover latent embedding generation, imputation, and diffusion or UMAP analyses.

Does the ENVI documentation include Python API references for custom spatial analysis scripts?▼

The ENVI documentation includes Python API references within its core materials, supporting scripts and assets directories for deeper customization and reproducible spatial transcriptomics workflows.

What are the limitations of using ENVI documentation for spatial transcriptomics research?▼

ENVI documentation provides consolidated learning materials and tutorials but relies on reference files for core concepts, meaning users need basic Python familiarity to fully execute and customize the provided spatial analysis workflows.