Bering - Segmentaion of Spatial Single Cell in Python

Bering is a tool for the segmentation on single-cell spatial data. It builds on top of torch_geometric and scanpy, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.

Manuscript

Please refer to our manuscript ([Jin, Zhang et al., 2023, bioRxiv](https://www.biorxiv.org/content/10.1101/2023.09.19.558548v1)) for more details.

Bering’s key applications

• Identify background and real signals in noisy spatial data.

• Identify cell annotations for transcripts on single-cell spatial data.

• Efficiently cell segmentation with cell annotations.

• Build and fine-tune pre-trained model on new data.

Getting started with Bering

• Browse Tutorials and Examples.

• Discuss usage on discourse and development on github.

Contributing to Bering

We are happy about any contributions! Before you start, check out our contributing guide.