Spatial transcriptomics annotation at single-cell resolution

SPASCER was designed to help understand the heterogeneity of tissue organizations, region-specific microenvironment, and intercellular interactions across tissue architectures at multiple levels. SPASCER contains datasets from 43 studies, including 1 082 sub-datasets from 16 organ types across four species. scRNA-seq was integrated to deconvolve/map spatial transcriptomics, and processed with spatial cell-cell interaction, gene pattern and pathway enrichment analysis. Cell-cell interactions and gene regulation network of scRNA-seq from matched spatial transcriptomics were performed as well.SPASCER 数据集旨在助力解析多维度下各类组织架构中的组织异质性、区域特异性微环境与细胞间相互作用。该数据集收录了来自43项研究的原始数据集，涵盖跨越4个物种的16种器官类型的1082个子数据集。研究整合了单细胞RNA测序（single-cell RNA sequencing，scRNA-seq）数据以实现空间转录组（spatial transcriptomics）的反卷积与映射，并针对空间细胞间相互作用、基因模式及通路富集分析开展了数据处理。此外，还针对匹配空间转录组的scRNA-seq数据开展了细胞间相互作用与基因调控网络分析。

搜集汇总

背景与挑战

背景概述

SPASCER是一个单细胞分辨率空间转录组注释数据库，旨在通过整合单细胞RNA测序数据，解析组织架构的空间异质性。该数据库包含来自43项研究的1082个数据集，涵盖16种器官和四个物种，并提供了空间细胞互作、基因调控网络和通路富集等分析功能，以支持对健康和疾病组织生物过程的理解。