omicverse-reference-label-transfer

Transfer cell-type labels from reference to query AnnData objects.

13|2|Updated Apr 5, 2026
One-click install
npx skills add https://github.com/omicverse/omicverse-skills --skill omicverse-reference-label-transfer-omicverse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: omicverse-reference-label-transfer
Source: https://github.com/omicverse/omicverse-skills/tree/main/src/omicverse_skills/skills/reference-label-transfer
Command: npx skills add https://github.com/omicverse/omicverse-skills --skill omicverse-reference-label-transfer-omicverse

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill removes the manual work of transferring cell-type labels from a labeled reference AnnData object onto an unlabeled query AnnData object in OmicVerse.

Core Features & Use Cases

  • Paired query/reference handling: Builds a shared integrated space from matching gene names and a reference cell-type column.
  • Multiple transfer backends: Supports harmony, scVI, and scanorama paths for different integration needs.
  • Built-in validation: Checks preprocessing, integrated embeddings, and branch-specific prediction and uncertainty keys before downstream plotting.
  • Use case: A researcher has a query dataset and a curated reference atlas and wants fast, reproducible cell annotation with uncertainty scores.

Quick Start

Give me my query and reference AnnData objects with a celltype column, and use this skill to run OmicVerse label transfer and return the predicted labels and uncertainty values.

Frequently Asked Questions about omicverse-reference-label-transfer

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

FAQPage Schema
How do I transfer cell-type labels from a reference onto a query AnnData object?▼

To transfer cell-type labels, map a reference AnnData object onto a query AnnData object using shared gene names and a reference cell-type column. This produces predicted labels and uncertainty values for single-cell datasets.

What is the best way to integrate single-cell datasets using harmony or scVI?▼

Integrating single-cell datasets requires selecting a transfer backend like harmony, scVI, or scanorama. These methods build a shared integrated space to map reference labels onto query cells for annotation.

Does label transfer in OmicVerse provide uncertainty scores for predicted cell types?▼

Label transfer in OmicVerse provides uncertainty scores alongside predicted cell types. It validates branch-specific prediction and uncertainty keys before downstream plotting to ensure reproducible cell annotation.

What do I need to prepare before running single-cell label transfer?▼

Before running label transfer, you need paired query and reference AnnData objects with shared gene names and a reference cell-type column. AnnotationRef preprocessing and training are also required to validate branch-specific keys.

Why does single-cell label transfer fail when using unmatched gene names?▼

Single-cell label transfer fails with unmatched gene names because it requires shared gene names to build a shared integrated space. Preprocessing validation checks ensure reference and query AnnData objects are compatible before integration.

Can I use scanorama for label transfer instead of harmony?▼

You can use scanorama for label transfer instead of harmony. The workflow supports harmony, scVI, and scanorama transfer branches to accommodate different single-cell dataset integration needs and produce prediction outputs.