articleNature MethodsJan 31, 2022HYBRID OA

Squidpy: a scalable framework for spatial omics analysis

GPGiovanni PallaHSHannah SpitzerMKMichal KleinDSDavid S. FischerACAnna C. Schaar

Helmholtz Zentrum München · Technical University of Munich · +1 more institution

PubMed
Indexed incrossrefpubmed

Abstract

Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Flexible tools are required to store, integrate and visualize the large diversity of spatial omics data. 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 efficient infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data. Squidpy is extensible and can be interfaced with a variety of already existing libraries for the scalable analysis of…

Citation impact

1,059
total citations
FWCI
79.09
Percentile
100%
References
58
Citations per year

Authors

13

Topics & keywords

Topics
Keywords
  • Python (programming language)
  • Omics
  • Scalability
  • Computer science
  • Spatial analysis
  • Data science
  • Computational biology
  • Data mining
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
No related works found for this paper.

Funding