Squidpy: a scalable framework for spatial omics analysis.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 35102346.
- Also identified by DOI 10.1038/s41592-021-01358-2 and PMC identifier 8828470.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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 spatial omics data.
Medical subject headings
- Computational Biology
- Gene Expression Profiling
- Proteomics
- Software