计算生物学
转录组
计算机科学
类型(生物学)
生物
基因表达
基因
遗传学
生态学
作者
Zhihan Ruan,Weijun Zhou,Zhihong Liu,Jinmao Wei,Yichen Pan,Chaoyang Yan,Xiaoyi Wei,Wenting Xiang,Chengwei Yan,Shengquan Chen,Jian Liu
标识
DOI:10.1016/j.crmeth.2024.100841
摘要
Cell-type-specific domains are the anatomical domains in spatially resolved transcriptome (SRT) tissues where particular cell types are enriched coincidentally. It is challenging to use existing computational methods to detect specific domains with low-proportion cell types, which are partly overlapped with or even inside other cell-type-specific domains. Here, we propose De-spot, which synthesizes segmentation and deconvolution as an ensemble to generate cell-type patterns, detect low-proportion cell-type-specific domains, and display these domains intuitively. Experimental evaluation showed that De-spot enabled us to discover the co-localizations between cancer-associated fibroblasts and immune-related cells that indicate potential tumor microenvironment (TME) domains in given slices, which were obscured by previous computational methods. We further elucidated the identified domains and found that Srgn may be a critical TME marker in SRT slices. By deciphering T cell-specific domains in breast cancer tissues, De-spot also revealed that the proportions of exhausted T cells were significantly increased in invasive vs. ductal carcinoma.
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