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Abstract
The maintenance and transition of cellular states are controlled by biological processes. Here we present a gene set-based transformation of single cell RNA-Seq data into biological process activities that provides a robust description of cellular states. Moreover, as these activities represent species-independent descriptors, they facilitate the alignment of single cell states across different organisms.
Highlights
The maintenance and transition of cellular states are controlled by biological processes
Considering that cellular states are controlled by genetic regulatory mechanisms[2], we propose using biological process activities (BPAs) in place of the expression of individual genes in the scRNA-Seq data, which leverages an ensemble of dozens of related genes
Analysis in BPA space enables a straightforward comparison of cell states across platforms and species with very few parameter settings and without the need for predicting orthologs
Summary
The maintenance and transition of cellular states are controlled by biological processes. Considering that cellular states are controlled by genetic regulatory mechanisms[2], we propose using biological process activities (BPAs) in place of the expression of individual genes in the scRNA-Seq data, which leverages an ensemble of dozens of related genes. In this way, discrepancies in individual genes can be averaged out, yielding reproducible measurements unaffected by common technical noises such as batch effects[3] and drop-out events[4] (Fig. 1b–d). We demonstrate the utility of using BPAs to align human and mouse data sets to shed light on their comparative and species-specific biology in early embryo development and in the cell types comprising the immune system
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