CellTypist recapitulates cell type structure and biology of independent datasets.
Regularised linear models with Stochastic Gradient Descent provide fast and accurate prediction.
Scalable and flexible. Python-based implementation easy to integrate into existing pipelines.
A community driven encyclopedia for cell types.
With Python 3.6+ installed, get releases on PyPI or bioconda.
pip install celltypist
or
conda install -c bioconda -c conda-forge celltypist
Read the complete Usage Guide on the GitHub repo.
The typical workflow consists of selecting an input file and running the annotation process.
import celltypist
input_file = celltypist.samples.get_sample_csv()
#Run cell typing followed by majority voting.
predictions = celltypist.annotate(input_file, majority_voting = True)
#Examine the prediction results.
predictions.predicted_labels
With Python 3.6+ installed, get releases on PyPI or bioconda.
pip install celltypist
or
conda install -c bioconda -c conda-forge celltypist
You can run CellTypist from anywhere on the command line.
celltypist --indata /path/to/input_data --majority-voting