Bento: a toolkit for subcellular analysis of spatial transcriptomics data

Bento:空间转录组数据亚细胞分析工具包

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作者:Clarence K Mah #, Noorsher Ahmed #, Nicole A Lopez, Dylan C Lam, Avery Pong, Alexander Monell, Colin Kern, Yuanyuan Han, Gino Prasad, Anthony J Cesnik, Emma Lundberg, Quan Zhu, Hannah Carter, Gene W Yeo

Abstract

The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. We demonstrate MERFISH, seqFISH + , Molecular Cartography, and Xenium datasets. Bento is part of the open-source Scverse ecosystem, enabling integration with other single-cell analysis tools.

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