Squidpy: a scalable framework for spatial single cell analysis

作者：Giovanni Palla, Hannah Spitzer, Michal Klein, David S. Fischer, Anna C. Schaar, Louis B. Kuemmerle, Sergei Rybakov, Ignacio L. Ibarra, Olle Holmberg, Isaac Virshup, Mohammad Lotfollahi, Sabrina Richter, Fabian J. Theis · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2021 · DOI：10.1101/2021.02.19.431994 · 被引用次数：71 · 研究领域：Single-cell and spatial transcriptomics、Cell Image Analysis Techniques、Gene expression and cancer classification

Abstract Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins. Squidpy provides both infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data.