Inferring pathway activity from single-cell and spatial transcriptomics data with PaaSc
Fig 6
Scoring pathway activities in the presence of batch effects.
The analysis used the GSE96583 dataset, in which peripheral blood mononuclear cells (PBMCs) from systemic lupus erythematosus (SLE) patients under two biological conditions were profiled: control (ctrl) and interferon (IFN) stimulation (stim). (A, B) Dimensional reduction plots showing cell clustering grouped by cell type (A) and biological condition (B). (C) Evaluation of three pathway scoring methods (PaaSc, GSDensity, and CelliD) using the B cell activation pathway from Gene Ontology. Pathway scores were calculated for each method and normalized by relative rank to values between 0 and 1 (where 1 represents the highest score). The analysis focused on scores from B cells, and receiver operating characteristic (ROC) scores were calculated to assess how effectively each method distinguished between biological conditions on the basis of gene set scores. (D) Interferon pathway activity was calculated using the same approach as in (C), with scores compared between control and stimulated conditions across all cell types.