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omicverse-single-cell-batch-integration

Automate batch integration of preprocessed single-cell AnnData across multiple backends.

13|2|Updated Apr 5, 2026
Search Tags:#harmony#single-cell#combat#anndata#scanorama#scvi#batch-integration
One-click install
npx skills add https://github.com/Starlitnightly/omicverse-skills --skill omicverse-single-cell-batch-integration
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: omicverse-single-cell-batch-integration
Source: https://github.com/Starlitnightly/omicverse-skills/tree/main/src/omicverse_skills/skills/single-cell-batch-integration
Command: npx skills add https://github.com/Starlitnightly/omicverse-skills --skill omicverse-single-cell-batch-integration

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anndata, numpy, pandas, omicverse, scib_metrics, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Automates batch integration for preprocessed single-cell AnnData across multiple backends, enabling side-by-side comparison and benchmarking.

Core Features & Use Cases

  • Supports integration backends Harmony, Combat, Scanorama, scVI, CellANOVA, and Concord from a single callable workflow, streamlining technology comparisons.
  • Enables benchmarking by producing both integrated embeddings and non-integrated references for evaluation across methods.
  • Real-world use: compare batch correction strategies on a preprocessed AnnData with a batch column to select the best backend for downstream analysis.

Quick Start

Run the preprocessed AnnData through the batch-integration skill to compare Harmony, Combat, and ScVI backends and optionally run the Benchmarker.

Frequently Asked Questions about omicverse-single-cell-batch-integration

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

FAQPage Schema
How do I perform single-cell batch integration on preprocessed AnnData?▼

Single-cell batch integration applies to preprocessed AnnData with a batch column, utilizing multiple backends like harmony, combat, scanorama, and scVI to generate integrated embeddings for downstream analysis.

Can I compare different batch correction methods like harmony and scVI?▼

Yes, you can compare batch correction methods like harmony and scVI side-by-side. The workflow supports multiple backends and optional benchmarking using scib_metrics to evaluate and select the best strategy.

What inputs do I need to run scanorama or scVI batch integration?▼

Running scanorama or scVI batch integration requires explicit inputs for backend selection, PCA settings, and backend-specific prerequisites on your preprocessed AnnData object to return integrated embeddings.

Does this batch integration workflow support CellANOVA and Concord?▼

Yes, the batch integration workflow supports CellANOVA and Concord backends alongside harmony, combat, scanorama, and scVI, returning integrated embeddings or models as appropriate for the selected method.

Why do I need a non-integrated reference for single-cell batch benchmarking?▼

A non-integrated reference is needed for single-cell batch benchmarking to evaluate the effectiveness of integrated embeddings against the original data using scib_metrics for objective method comparison.

What are the limitations of using combat for single-cell batch integration?▼

Combat provides batch integration but requires explicit PCA settings and backend-specific prerequisites. Users must provide a preprocessed AnnData with a batch column to successfully generate integrated embeddings.

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