Uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles

Representation of single cells in biologically meaningfull terms has potential to improve classical analysis steps as well as give rise to multiple new applications. We have developed UniPath for representation of single-cell expression and open-chromatin profile using pathway enrichment scores. UniPath can also perform pseudo-temporal ordering of single-cells using their pathway enrichment-scores. We analysed several datasets using UniPath. Analysis of atlas of mouse single-cell RNAseq profiles with UniPath revealed surprising but biologically-meaningful convergence of different cell-types from distant organs. Overall design: We performed single cell RNA-seq for two types of cells from non-small cell lung cancer (NSCLC) cell-lines. Applying UniPath revealed the importance of enrichment and co-enrichment of several pathways in tumorogenicity of NSCLC.