GraphCompass: Spatial metrics for differential analyses of cell organization across conditions

Abstract excerpt

Spatial omics technologies are increasingly leveraged to characterize how disease disrupts tissue organization and cellular niches. While multiple methods to analyze spatial variation within a sample have been published, statistical and computational approaches to compare cell spatial organization across samples or conditions are mostly lacking. We present GraphCompass, a comprehensive set of omics-adapted graph a...

Topics

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• Advanced Proteomics Techniques and Applications
• Algorithms
• Bioinformatics and Genomic Networks
• Cluster Analysis
• Neural Networks, Computer
• Phenotype
• Radiomics and Machine Learning in Medical Imaging
• Single-cell and spatial transcriptomics

Identifiers and source

Literature Corpus work

88bcf5cb-99cb-5937-adeb-cf6ba0fc2e21

DOI

10.1101/2024.02.02.578605