multimodal intersection analysis ,MIA 多模式相交分析
    联合分析单细胞数据和空间转录组数据，两者信息进行结合
    分析获得的细胞亚群的标记基因集合和ST分析获得的不同区域标记基因集合进行比较并进行统计检验，即可获得不同亚群在空间区域中的分布。
    原始文献： Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas
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    MIA可以将不同亚群将ST的癌细胞亚群与scRNA-seq分群结果进行对应
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    MIA计算方法：
    This analysis proceeds by first delineating sets of cell type-specific and tissue region-specific genes and then determining whether their overlap is higher (enrichment) or lower (depletion) than expected by chance.
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    Determination of cell type enrichment/depletion by MIA.
    We queried the significance of the overlap between ST genes and cell type marker genes using the hypergeometric cumulative distribution, with all genes as the background to compute
    the P value. In parallel, we test for cell type depletion by computing −log10(1−P).

    MIA map:
    Extending this analysis to all pairs of cell types and tumor regions produces an ‘MIA map’.
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    To assess the robustness to the number of genes required for MIA maps, we found that when the number of detected genes in the cancer region was downsampled below 100 genes, an enrichment with fibroblast specific genes dropped below significance
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