convexgating 0.1.0

ConvexGating is a Python tool to infer optimal gating strategies for flow cytometry and cyTOF data.

Features

Convex gating is a Python package to infer an optimal gating strategy from flow, cyTOF or Ab/CITE-seq data. Convex gating expects a labelled input (for instance, from clustering) and returns a gating panel to separate the selected group of events (e.g. a cluster) from all other events (see Fig. 1a). For each cluster, it reports the purity (precision), yield (recall) and the harmonic mean of both metrics (F1 score) for each gate hierarchy and the entire gating strategy. It relies on the scanpy/anndata for the data format and data pre-processing and further on PyTorch for stochastic gradient descent. Therefore, resulting gates may slightly vary.

The iterative procedure to find a suitable gate before applying the convex hull is illustrated in the following graphic.

Installation

You can install convexgating via pip from PyPI:

$ pip install convexgating

Usage

Please see the Command-line Reference for details.

Credits

This package was created with cookietemple using Cookiecutter based on Hypermodern_Python_Cookiecutter.