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registration-paste

Align multiple spatial transcriptomics slices using PASTE optimal transport.

3|Updated Apr 3, 2026
Search Tags:#alignment#spatial-transcriptomics#paste#adata#multi-slice#slice-registration
One-click install
npx skills add https://github.com/chenyhvvvv/STAT-agent --skill registration-paste
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: registration-paste
Source: https://github.com/chenyhvvvv/STAT-agent/tree/main/stat_agent/skills/registration-paste
Command: npx skills add https://github.com/chenyhvvvv/STAT-agent --skill registration-paste

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Align multiple spatial slices across experiments by matching spots across slices using the PASTE method to enable joint analyses.

Core Features & Use Cases

  • PASTE-based alignment of multiple slices via optimal transport for cross-slice correspondence
  • Outputs aligned coordinates in adata.obsm['spatial_registered'] for integrated analysis
  • Visual overlays to compare before and after alignment across slices

Quick Start

Load at least two slices into your session and run the PASTE registration workflow to generate spatially registered coordinates.

Frequently Asked Questions about registration-paste

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

FAQPage Schema
How do I align multiple spatial transcriptomics slices across different experiments?▼

To align multiple spatial transcriptomics slices across experiments, use the PASTE optimal-transport method to match spots across slices and generate unified coordinates for joint cross-slice analyses.

What is the alpha parameter used for in PASTE slice registration?▼

The alpha parameter in PASTE slice registration controls the balance between gene expression similarity and spatial coordinates during optimal-transport-based pairwise alignment, allowing you to tune the alignment sensitivity.

Do I need to normalize spatial transcriptomics data before running PASTE alignment?▼

Yes, you must load at least two spatial transcriptomics slices into your session, identify common genes, and normalize the data before running the PASTE alignment workflow to ensure accurate spot matching.

Where are the aligned coordinates stored after running PASTE on multi-slice adata objects?▼

After running PASTE alignment on multi-slice adata objects, the aligned spatial coordinates are output to adata.obsm['spatial_registered'], making them immediately available for downstream integration and visual overlays.

Can I visualize spatial transcriptomics slices before and after PASTE alignment?▼

Yes, the PASTE registration workflow provides visual overlays to compare spatial transcriptomics slices before and after alignment, helping you verify the cross-slice correspondence and integration quality.

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