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- Click the counts data node
- Click the Exploratory analysis section of the toolbox
- Click Graph-based clustering
- Configure the parameters
- Click Finish to run
Graph-based clustering produces a Clustering result data node. The task report lists the cluster results and cluster statistics (Figure 1). If clustering was run with Split cells by sample enabled on a single cell counts data node, the cluster results table displays the number of clusters found for each sample and clicking the sample name opens the sample-level report.
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The Clustering result data node includes the input values for each gene and adds cluster assignment as a new attribute, Graph-based, for each observation. If the Clustering result data node is visualized by Scatter plot, PCA, t-SNE, or UMAP, the plot will be colored by the Graph-based attribute and the group biomarker table, if generated, will be included below the plot (Figure 2).
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Basic Graph-based clustering parameters
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Choose which version of the Louvain clustering algorithm to use. Options are Louvain [1], Louvain with refinement [2], and SLM [3]. The most recent version is Smart Local Moving (SLM). The default is Louvain.
Compute biomarkers will determine biomarkers for compute features that are highly expressed when comparing each cluster.
Split cells by sample
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Overview
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