Quantitative representation of pathways across cell-types allows to identify uncharacterized subsets

Gene expression profiles hold meaningful information regarding functional and phenotypic diversity of the human body. In the last decade, we are witnessing a dramatic increase in gene expression data that have become available as a result of significant progress in high throughput sequencing technologies, such as single-cell RNA sequencing (scRNA-seq). Here, we utilized gene expression profiles of individual cells to associate biological pathways to different cell types within tissues, and by that help in their characterization. We analyzed scRNA-seq data of muscle, kidney and mammary gland of mice. Specifically, we associated pathways with cell subsets by using a scoring scheme that we developed, which is based on the differential expression of pathway genes across tissues. The association of pathways with cell subsets illuminated functional differences between cell subsets and contributed to the functional annotation of previously uncharacterized cell subsets. Our results emphasize the importance of pathways perspective to computational analyses of cell subsets.