Differential Expression Analysis (DEA)

To begin, you must first select the Number of Genes to be plotted per cluster (maximum of 8) (1) and the Statistical Method to be employed (Wilcoxon or t-test) (2). Optionally, you can define a custom Gene List to visualize (3). Once your selections are made, click Run (4) to start the analysis. After running, a link titled Differential Expression Analysis will appear above (5), allowing you to download the complete DEA results per cluster. Below (6), two Dot Plot visualizations will be generated. In these plots, dot color indicates whether the gene is up- or down-regulated, while dot size reflects the percentage of cells within each cluster that express the gene. By default, the analysis filters results to display only genes with an adjusted p-value < 0.05. For each gene and cluster, the following are computed: Mean expression (average expression among expressing cells) Log fold change (logFC) comparing expression in the target cluster vs. all other clusters Only genes with a logFC ≥ 0.25 and mean expression ≥ 0.1 are considered for visualization, unless a custom list is provided. Finally, click Continue to Visualization (7) to plot selected genes in UMAP or PCA space for spatial insight.