Projecting clumped transcriptomes onto single cell atlases to achieve single cell resolution
Projecting clumped transcriptomes onto single cell atlases to achieve single cell resolution
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DOI：
10.1101/2022.04.26.489628
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
Nelson Johansen;G. Quon
中科院分区：
文献类型：
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作者：
Nelson Johansen;G. Quon
多模态单细胞RNA分析捕获RNA含量以及其他数据模式，如细胞的空间位置或细胞的电生理特性。然而，与专用的scRNA-seq测定相比，它们可能无意中捕获来自多个相邻细胞的RNA，与scRNA-seq相比，它们表现出较低的RNA测序深度，或者缺乏全基因组RNA测量。我们提出了scProjection，一种将单个多模态RNA测量映射到深度测序的scRNA-seq图谱的方法，以提取细胞类型特异性的单细胞基因表达谱。我们展示了scProjection的几个用例，包括从空间转录组分析中识别空间基序，在空间和多模态单细胞分析中区分邻近细胞的RNA贡献，以及从基因标记中输入未测量基因的表达测量。因此，scProjection结合了多模态和scRNA-seq测定的优点，可以对单个细胞进行精确的多模态测量。
Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including the identification of spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.