Niche-DE: niche-differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions.

Niche-DE: niche-differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions.
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DOI:
10.1186/s13059-023-03159-6
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发表时间:
2024-01-12
期刊:
影响因子:
12.3
通讯作者:
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中科院分区:
生物学1区
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现有的空间转录组学数据分析方法侧重于描绘整个组织中细胞类型的全局基因表达变化,而不是由细胞-细胞相互作用驱动的局部基因表达变化。我们提出了一个新的统计程序,称为小生境差异表达(小生境DE)分析,确定细胞类型特异性的小生境相关基因,这是差异表达的特定细胞类型的背景下,特定的空间小生境。我们进一步开发了小生境LR,一种揭示小生境差异基因表达模式背后的配体-受体信号传导机制的方法。小生境-DE和小生境-LR适用于低分辨率基于斑点的空间转录组学数据和分辨率为单细胞或亚细胞的数据。在线版本包含补充材料,可通过10.1186/s13059-023-03159-6获得。
Existing methods for analysis of spatial transcriptomic data focus on delineating the global gene expression variations of cell types across the tissue, rather than local gene expression changes driven by cell-cell interactions. We propose a new statistical procedure called niche-differential expression (niche-DE) analysis that identifies cell-type-specific niche-associated genes, which are differentially expressed within a specific cell type in the context of specific spatial niches. We further develop niche-LR, a method to reveal ligand-receptor signaling mechanisms that underlie niche-differential gene expression patterns. Niche-DE and niche-LR are applicable to low-resolution spot-based spatial transcriptomics data and data that is single-cell or subcellular in resolution. The online version contains supplementary material available at 10.1186/s13059-023-03159-6.
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