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The Maximum modularity is a measure of the quality of the clustering result. Modularity measures how much cells /samples within a cluster are similar to each other and less similar to cells /samples in other clusters. Higher modularity indicates a better  result. Optimal modularity is 1. 

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The total number of clusters is listed along with the number and percentage of observations ( cells /samples) in each cluster. 

Top marker features per cluster

Biomarkers for each cluster are calculated using an ANVOA test where each cluster is compared to the other cells/samples in cells in the data set, genes with fold-change > 1.5 are included, and these genes are sorted by ascending p-value (ties broken by greater fold change). The top 10 genes for each cluster are shown in the table. The full ANOVA results can be obtained by clicking the Run ANOVA button, which will generate a Feature list data node. 

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