Related Experiment Video
Updated: Jun 13, 2025
Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
Published on: February 23, 2018
Bin2cell reconstructs cells from high resolution Visium HD data
Krzysztof Polański1,2, Raquel Bartolomé-Casado2,3, Ioannis Sarropoulos1,2
1Cambridge Stem Cell Institute and Department of Medicine, University of Cambridge, Cambridge, CB2 0AW, United Kingdom.
Summary:
Visium HD by 10X Genomics is the first commercially available platform capable of capturing full scale transcriptomic data paired with a reference morphology image from archived FFPE blocks at sub-cellular resolution. However, aggregation of capture regions to single cells poses challenges. Bin2cell reconstructs cells from the highest resolution data (2 μm bins) by leveraging morphology image segmentation and gene expression information. It is compatible with established Python single cell and spatial transcriptomics software, and operates efficiently in a matter of minutes without requiring a GPU. We demonstrate improvements in downstream analysis when using the reconstructed cells over default 8 μm bins on mouse brain and human colorectal cancer data.
Availability And Implementation:
Bin2cell is available at https://github.com/Teichlab/bin2cell, along with documentation and usage examples, and can be installed from pip. Probe design functionality is available at https://github.com/Teichlab/gene2probe.
