SOTIP is a versatile method for microenvironment modeling with spatial omics data

Zhiyuan Yuan; Yisi Li; Minglei Shi; Fan Yang; Juntao Gao; Jianhua Yao; Michael Q. Zhang

doi:10.1038/s41467-022-34867-5

Nature Communications (Nov 2022)

SOTIP is a versatile method for microenvironment modeling with spatial omics data

Zhiyuan Yuan,
Yisi Li,
Minglei Shi,
Fan Yang,
Juntao Gao,
Jianhua Yao,
Michael Q. Zhang

Affiliations

Zhiyuan Yuan: Institute of Science and Technology for Brain-Inspired Intelligence; MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence; MOE Frontiers Center for Brain Science, Fudan University
Yisi Li: MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, BNRist; Department of Automation, Tsinghua University
Minglei Shi: MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, School of Medicine, Tsinghua University
Fan Yang: Tencent AI Lab
Juntao Gao: MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, BNRist; Department of Automation, Tsinghua University
Jianhua Yao: Tencent AI Lab
Michael Q. Zhang: MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, BNRist; Department of Automation, Tsinghua University

DOI: https://doi.org/10.1038/s41467-022-34867-5
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 19

Abstract

Read online

Methods that analyse heterogeneity and compare tissue microenvironments using spatial omics data are challenging to develop. Here, the authors present SOTIP, a method that can perform spatial heterogeneity, spatial domain, and differential microenvironment analyses across multiple spatial omics modalities.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal