SCS: cell segmentation for high-resolution spatial transcriptomics.

ABSTRACT: Spatial transcriptomics promises to greatly improve our understanding of tissue organization and cell-cell interactions. While most current platforms for spatial transcriptomics only offer multi-cellular resolution, with 10-15 cells per spot, recent technologies provide a much denser spot placement leading to sub-cellular resolution. A key challenge for these newer methods is cell segmentation and the assignment of spots to cells. Traditional image-based segmentation methods are limited and do not make full use of the information profiled by spatial transcrip-tomics. Here we present SCS, which combines imaging data with sequencing data to improve cell segmentation accuracy. SCS assigns spots to cells by adaptively learning the position of each spot relative to the center of its cell using

SUBMITTER: Chen H 

PROVIDER: S-EPMC10312435 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature