Spatial S5 Downstream

Community

QING1105

spatial-s5-downstream

Stage 5 of the spatial transcriptomics workflow — neighborhood enrichment and cell-cell communication analysis. Use when the user asks to compute cell-type neighborhood enrichment (co-localization) or infer cell-cell communication with CellChat on Visium data. Produces enrichment heatmaps and CellChat network plots, then stops for review.

Overview

Publisher	QING1105
Repository	`ezST`
Skill name	`spatial-s5-downstream`
Stars	101
Forks	1
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by QING1105 on GitHub. Read the source before you install it.

Installation

Install the Spatial S5 Downstream AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/QING1105/ezST/tree/master/plugins/spatial-transcriptomics/skills/s5-downstream
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/QING1105/ezST/tree/master/plugins/spatial-transcriptomics/skills/s5-downstream

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/QING1105/ezST.git /tmp/ezST
mkdir -p .claude/skills
cp -r /tmp/ezST/plugins/spatial-transcriptomics/skills/s5-downstream .claude/skills/spatial-s5-downstream

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spatial S5 Downstream in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Spatial S5 Downstream on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Spatial S5 Downstream is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

S5 — Downstream (Neighborhood + Communication)

Goal

Quantify cell-type co-localization with neighborhood enrichment, and infer spatially proximal cell-cell communication with CellChat v2.

Prerequisites

Deconvolved Visium h5ad from S4 with cell-type proportions (for both analyses).
R + CellChat v2 for communication (see install_r_packages_spatial.R).

Steps

Neighborhood enrichment: spatial_neighborhood_enrichment(adata_path=..., cell_type_key=..., output_path=..., plot_path=..., n_neighs=...)
- Defaults: n_neighs=6.
- Output: enrichment z-score table + heatmap.
CellChat: infer_spatial_cell_communication(st_h5ad=..., cell_type_key=..., output_dir=..., plot_path=..., r_script_path=..., species=...)
- species: "human" (default) or "mouse" — selects the CellChatDB.
- Output: CellChat object, communication summary, network/heatmap plots.

Outputs

results/08_neighborhood/<sample>_enrichment.csv + heatmap PNG
results/09_communication/<sample>_cellchat_*.png (network, heatmap, bubble)
results/09_communication/<sample>_communication_summary.csv

Biological Interpretation

Neighborhood: which cell-type pairs co-localize significantly (|z| > 2)? Does this match known tissue niches (e.g., tumor–macrophage, T cell–APC)?
Communication: which ligand–receptor pairs dominate? Are they consistent with the tissue's known biology (e.g., immune checkpoint pairs in tumor)?

Stop for Review

Present interpretation using the template from the parent spatial-transcriptomics skill. This is the final stage — after review, produce the overall workflow summary.

Frequently asked questions

What does the Spatial S5 Downstream AI skill do?

Why use Spatial S5 Downstream on TypingMind?

Because you install it once and use it with any model. Spatial S5 Downstream is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Spatial S5 Downstream in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/QING1105/ezST/tree/master/plugins/spatial-transcriptomics/skills/s5-downstream. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Spatial S5 Downstream?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Spatial S5 Downstream?

As many as you like. As long as a model supports skills, you can use Spatial S5 Downstream with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Spatial S5 Downstream AI skill free?

Yes. It is published on GitHub by QING1105 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

S5 — Downstream (Neighborhood + Communication)

Goal

Prerequisites

Steps

Outputs

Biological Interpretation

Stop for Review

Frequently asked questions

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