Fig. 5: Analysis results in the mouse neuronal cell scRNA-seq data.
Results are shown for comparing nonpeptidergic nociceptors 1 (NP1) versus all the other cell types. a p-values from iDEA for GSE analysis display expected enrichment of small p-values (for true signals) and a long flat tail towards large p-values. b Quantile-quantile plots of −log10(p-values) from GSE methods including iDEA (orange), fGSEA (green), CAMERA (navyblue), PAGE (skyblue) and GSEA (yellow) are shown under permuted null. The p-values from iDEA, fGSEA, PAGE and GSEA are reasonably well calibrated, while that from CAEMRA are overly conservative. Here λgc is the genomic control factor. c Number of identified enriched gene sets by iDEA (orange), fGSEA (green), CAMERA (navyblue), PAGE (skyblue) and GSEA (yellow) are plotted against different empirical false discovery rates (FDR). iDEA is more powerful than other methods for GSE analysis. d Number of identified DE genes by iDEA (orange) and zingeR (blue) are plotted against different empirical FDR values. iDEA is more powerful than zingeR for DE analysis. e Heatmap shows the normalized expression level (log10-transformation with pseudo-count 0.1) for selected 50 DE genes (rows) identified by iDEA for cells in the two cell types (columns). Genes are sorted by Hierarchical clustering, cells are ordered by cell types (NP1: red; others: other colors). These DE genes clearly distinguish two compared cell types. f Bubble plot shows –log10(p-values) for GSE analysis from iDEA (y-axis) for different gene sets. Gene sets are colored by four categories: GO biological process (orange), GO molecular function (blue), GO cellular component (green) and other gene ontology terms with only GO numbers (yellow). The size of the dot represents the number of genes contained in the gene set. Names for ten of the gene sets that are closely related to nociceptive sensory neurons’ activities are highlighted in the panel.
