Graduate Group in Computer Science, University of California, Davis, Davis, CA, USA.
Integrative Genetics and Genomics Graduate Group, University of California, Davis, Davis, CA, USA.
Nat Commun. 2023 Aug 25;14(1):5192. doi: 10.1038/s41467-023-40744-6.
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 identifying 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.
多模态单细胞 RNA 检测可捕获 RNA 内容以及其他数据模态，如空间细胞位置或细胞的电生理特性。然而，与专用的 scRNA-seq 检测相比，它们可能会无意中捕获来自多个相邻细胞的 RNA，与 scRNA-seq 相比，RNA 测序深度较低，或者缺乏全基因组 RNA 测量。我们提出了 scProjection，这是一种将单个多模态 RNA 测量映射到深度测序的 scRNA-seq 图谱以提取细胞类型特异性单细胞基因表达谱的方法。我们展示了 scProjection 的几个用例，包括从空间转录组检测中识别空间模式，区分空间和多模态单细胞检测中来自相邻细胞的 RNA 贡献，以及从基因标记推断未测量基因的表达测量。因此，scProjection 将多模态和 scRNA-seq 检测的优势结合起来，为单细胞提供精确的多模态测量。
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