Measuring Cell Type Similarity with Gene Ontology in Single-Cell RNA-Seq
standard seurat analysis on GO_seurat object
calculate correlation between cell types represented by scaled GO, per...
calculate cross-species correlation between cell types represented by ...
get requested ensembl ID to GO mapping table
get per cell type average scaled vector of GO terms
get shared up and down regulated GO terms for all pairs of cell types
query co-up and co-down regulated GO terms from certain cell type pair...
record some global variables: pre-defined column name in biomaRt query...
create a seurat object with GO terms
plot clustered heatmap for cell type corr
plot Sankey diagram for cell type links above a certain threshould
Traditional methods for analyzing single cell RNA-seq datasets focus solely on gene expression, but this package introduces a novel approach that goes beyond this limitation. Using Gene Ontology terms as features, the package allows for the functional profile of cell populations, and comparison within and between datasets from the same or different species. Our approach enables the discovery of previously unrecognized functional similarities and differences between cell types and has demonstrated success in identifying cell types' functional correspondence even between evolutionarily distant species.
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