What is cell type annotation?

Cell type annotation is the process of identifying and labeling different cell types in single-cell RNA sequencing (scRNA-seq) data by analyzing gene expression patterns. It's a crucial step in single-cell analysis that assigns biological meaning to cell clusters.

How does AI improve scRNA-seq annotation?

AI-powered annotation leverages large language models trained on extensive biological literature to provide accurate, context-aware cell type identification. Multiple AI models work in consensus to reduce bias and improve annotation reliability compared to single-method approaches.

What file formats does mLLMCelltype support?

mLLMCelltype supports CSV, TSV, and Excel (.xlsx) formats containing marker genes identified from your scRNA-seq analysis. Upload your top differentially expressed genes per cluster, with files up to 16MB in size.

How accurate is automated cell type annotation?

mLLMCelltype achieves 94.2% average accuracy across diverse datasets, with 96.8% accuracy for major cell types. The multi-model consensus approach provides confidence scores for each annotation, helping identify results that may need manual review.

Is mLLMCelltype free to use?

Yes, mLLMCelltype is a free, open-source tool for the research community. Users need to provide their own API keys for the AI models they wish to use (GPT-4, Claude, Gemini, etc.).

AI-Powered Cell Type Annotation Platform

Advanced scRNA-seq annotation using multiple LLMs for accurate single cell analysis

Multi-Model Cell Type Annotation

Leverage multiple AI models for accurate scRNA-seq annotation and cell identification

Consensus-Based Annotation

Advanced consensus mechanism ensures reliable cell type annotation results

Secure scRNA Analysis

Bank-level security for your single-cell RNA sequencing data and API keys