hello，大家好，最近看一些文章，越来越多的空间转录组文章开始进行空间位点的细胞类型注释，如下图：
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也就是说，对单点的空间位置进行注释，看来这是一个趋势，当然之前也分享了很多注释的方法，包括单细胞的，空间的，等等，而我们今天分享的内容参考的文献是Identification of HSC/MPP expansion units in fetal liver by single-cell spatiotemporal transcriptomics,里面的内容很经典，方法很好，值得大家深入读一读。今天我们来分享其中关键的空间细胞注释和临近通讯的问题。
首先来看空间细胞注释
当然，这里也离不开单细胞的数据，单细胞研究的生物学意义这里不再赘述，大家可以看文章Identification of HSC/MPP expansion units in fetal liver by single-cell spatiotemporal，这篇文章是对文献生物意义的解读，大家可以看一下，作为生信人员，比较关注其生信的分析方法。单细胞的分析我们就不再多讲，直接从注释好的单细胞数据和配套的空间转录组数据联合分析开始。
To show the spatial organization of principal cell types in an unbiased manner, we performed deconvolution analysis by assigning an enrichment score for each spot with cell type signature genes derived from scRNA-seq（解卷积的方法，具体的方法我们后面分享）。After deconvolution, two spot patterns (first pattern and second pattern) were shown based on the enrichment score of the top two cell types, and then mapped to the original FL region。（这个地方很有意思，top2的模式用来研究，之前我们的认知都在top1）.
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根据上图的结果我们可以看出来一些主要的细胞类型的分布（As expected, erythroid cells and hepatoblasts showed the highest enrichment score in most spots, indicating that they are the predominated cell components of FL）。当然，这里的空间位置主要是用来验证临近通讯。we regarded the spots as credible for one cell type, if the enrichment score of those cell types is higher than a threshold (80% to HSCs/ MPPs and 70% to niche cells), and then mapped them to the original FL region（分数的前五分之一是单纯的一种细胞类型，这个注释在之前的文章中给大家分享过）。To evaluate the performance of ST in resolving spatial organization, we examined the expression of cell type-specific genes in the candidate spots（外加marker gene 的验证）。而最终的注释目的在于further decoding cell–cell interactions predicted by scRNA-seq。
确定细胞间相互作用的架构基础，we defined HSC/MPP-localized spots as intra-spots (indicating the closest relationship), HSC/MPP-surrounded spots as inter-spots (indicating the second closest relationship), and other distant spots (indicating nearly no interactive relationship) (三种空间位置关系，点内，临近和远距离的spot).
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这个时候就会涉及到之前一直重点关注的问题，细胞之间的距离问题。For each niche cell type, analysis of enrichment score for different types of spots showed that EC with the highest score for intraspots was close to HSCs/MPPs, which is consistent with a previous report；hepatoblast and stromal cell with the highest scores respectively for inter-spots and other distant spots were less close to HSCs/MPPs;（细胞类型之间的距离有远有近，距离很近的细胞类型关系密切，可能在密谋什么大事😄）。unexpectedly, macrophage with higher scores for intra- and inter-spots than that for other distant spots was considered as a novel niche component spatially close to HSCs/MPPs（这也是作者发现的一个新的点），为了衡量这个HSCs/MPPs（目标细胞）和周围细胞（niche cells）的关系，we defined an enrichment fold based on the ratio of the enrichment score median for each spot type to the enrichment score median for all spots. Consequently, we found that macrophage showed a 11.52-fold enrichment in the intra-spots and a 1.31-fold in the inter-spots, EC showed a 1.62-fold enrichment in the intra-spots, while hepatoblast and stromal cell showed less enrichment in the intra-spots（其实这里就是周围细胞的含量丰度）。
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当然，作者也用了其他手段来验证空间上细胞位置之间的距离关系，其中就包括CSOmap这个软件，这个软件由张泽民团队开发的，大家感兴趣可以试一下，Taken together, the results from three analytic methods of spatial information support that macrophage serve as an important niche cell with the closest relationship with HSCs/MPPs.
接下来就是空间位置 + 临近通讯了。
At molecular level, we examined the spatial expression of interactive signals predicted by CellPhoneDB analysis, and found that genes encoding ligands, such as MDK and PTN, were highly expressed in niche cells of intra-spots and inter-spots。
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这些结果表明空间邻近性促进了功能上支持 HSC/MPP 扩展的信号交互。 鉴于点内和点间的特征在于细胞之间的空间接近性和丰富的交互信号，我们将它们定义为扩展单元，其中 HSC/MPP 位于点的核心并与周围的生态位细胞点相互作用。（思路不错，值得借鉴）。
综上所述，我们证明 FL HSCs/MPPs 以多个单位扩展，其中巨噬细胞和多种生长因子（包括 MDK 和 PTN）高度富集。
当然生信方法上，空间注释还是以来seurat包的单细胞空间联合的分析方法，很常见了，但是需要注意一点，This probabilistic transfer procedure was implemented using the FindTransferAnchors (dims = 1:30) and TransferData (dims= 1:30) functions in Seurat with the combination of top 100 DEGs of each cell type.（在选择多少个基因代表一种细胞类型的时候，这个数量可以借鉴）。
生活很好，有你更好
