StereoSiTE: a framework to spatially and quantitatively profile the cellular neighborhood organized iTME.

ABSTRACT:

Background

Spatial transcriptome (ST) technologies are emerging as powerful tools for studying tumor biology. However, existing tools for analyzing ST data are limited, as they mainly rely on algorithms developed for single-cell RNA sequencing data and do not fully utilize the spatial information. While some algorithms have been developed for ST data, they are often designed for specific tasks, lacking a comprehensive analytical framework for leveraging spatial information.

Results

In this study, we present StereoSiTE, an analytical framework that combines open-source bioinformatics tools with custom algorithms to accurately infer the functional spatial cell interaction intensity (SCII) within the cellular neighborhood (CN) of interest. We applied StereoSiTE to decode ST dat

SUBMITTER: Liu X 

PROVIDER: S-EPMC11503478 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature