Fig. 4: scMerge2 enables differential cell state detection for multi-condition data.
From: Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2
a, b UMAP plot of integrated COVID-19 data coloured by (a) differential abundance (DA) probability scores calculated by DA-seq between the moderate and severe patients, where higher scores indicated the cells are more related to severe states; b DA region associated with disease severity identified by DA-seq. c Enrichment scores of selected pathways for cell-type-specific differential expressed genes distinguished the severity, where a higher score indicates a higher enrichment associated with severe states. The size of the dot indicates the −log10 adjusted p-value, where black circles indicate statistical significance (Benjamini-Hochberg adjusted p-value < 0.05) from two-sided gene set enrichment test using R package fgsea; and the colour indicates the normalised enrichment scores of the pathways. d Scatter plots showing per-sample gene set signatures (Type-1 IFN) calculated from the scMerge2 normalised data along the days since symptom onset, coloured by disease severity of the patient. CD14 Monocytes, CD4 CM and CD4 Naive are shown as examples. Source data are provided as a Source Data file.
