Universal Cell
Classification
MiraTyper delivers fast, accurate, and reproducible cell classification across hundreds of cell types, multiple data modalities, and diverse tissues—without tissue-specific model selection.
Cell Typing is Broken
Current approaches create significant bottlenecks that slow down research and introduce errors.
Slow & Manual
Teams spend weeks hand-labeling cells. Manual pipelines are fragile, time-consuming, and error-prone.
Inconsistent Results
Public tools are slow, inconsistent across studies, and require tissue-specific model selection.
Batch Effects
Accuracy and reproducibility suffer across different sequencing platforms and donors.
Better. Faster. Flexible.
A single universal model that works across tissues, platforms, and species.
High-Fidelity
Reproducible phenotyping across hundreds of cell types with hierarchical F1 scores of 0.84–0.99.
Lightning Fast
From hours to minutes. Process ~110M cells in 30 minutes. 30k cells in under 1 minute on CPU.
Universal Model
No manual model selection required. Works across tissues, platforms (10x, CosMx, Visium), and species.
MiraTyper vs. Current Methods
See how MiraTyper compares to traditional cell typing approaches.
| Feature | Current Methods | MiraTyper |
|---|---|---|
| Approach | Marker-based / Cluster-based | Marker/Cluster Agnostic |
| Batch Effects | Susceptible to batch variation | Batch resistant |
| Platform Support | Technology-specific (10x, CosMx) | Cross-platform compatible |
| Tissue Scope | Tissue-specific models required | Cross-tissue with one model |
| Rare Cell Types | Difficult to detect | Excellent detection |
| Model Selection | Many models / manual selection | Single unified model |
| Label Harmonization | Manual normalization required | Pre-harmonized CL ontology |
Validated Benchmarks
Independently validated against CellTypist using hierarchical F1 metrics on real-world datasets.
Blood (Immune)
Single-cell mapping of human ureter immune subset (Fink et al. 2022)
Brain (Neocortex)
Transcriptomic cytoarchitecture of human neocortex (Jorstad 2023)
Built on Cutting-Edge AI
MiraTyper combines hybrid generative AI embeddings with transformer-based classification.
100M+ Cell Training
Trained on CellXGene corpus with rigorous quality control
CL Ontology Labels
Pre-harmonized Cell Ontology labels with confidence scores
Zero-Shot Learning
Handles rare and novel cell types without retraining
Multi-Platform
10x Genomics, CosMx, Visium, and more
Accelerate Your Research
MiraTyper powers discovery and development across the drug and diagnostics pipeline.
Drug Discovery
Identify detailed cell types and disease states in your proprietary or public data sets. Harmonize data sets across batches and technologies.
Pathology Model Training
Identify image patches with detailed cell mixtures using spatial transcriptomics data.
Diagnostic Development
Fine tune classifiers on novel conditions and utilize confidence metrics to identify atypical cell states.
Biomarker Discovery
Identify disease-associated cell states and rare populations with high precision.
Ready to Transform Your Cell Analysis?
Get started with MiraTyper today. Available as a Docker package or through our user-friendly application.