CellTypist
An automated cell type annotation tool for single-cell RNA-seq data using logistic regression classifiers.
What is CellTypist?
CellTypist is an automated cell type annotation tool designed for single-cell RNA sequencing (scRNA-seq) data analysis. It uses logistic regression classifiers optimized by stochastic gradient descent to predict cell types and subtypes from gene expression profiles, helping researchers interpret cellular heterogeneity in complex tissues. The tool supports both built-in models (with a focus on immune cells) and custom-trained models for specialized applications.
Bioinformaticians, computational biologists, and researchers analyzing single-cell RNA-seq data who need accurate and scalable cell type annotation, particularly those working with immune cell datasets or requiring custom classification models.
Developers choose CellTypist for its interpretable logistic regression approach, flexibility in model training and cross-species conversion, and seamless integration with popular single-cell analysis ecosystems like Scanpy and AnnData, enabling reproducible and customizable workflows.
Overview
A tool for semi-automatic cell type classification
Use Cases
Best For
- Automating cell type annotation for large-scale single-cell RNA-seq datasets
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