Hang Zhang; Yi Zhang; Kai Ming Ting; Jie Zhang; Qiuran Zhao

Kernel-bounded clustering for spatial transcriptomics enables scalable discovery of complex spatial domains

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Figure 4.

Examining the ability to find clusters of varied densities and overlapping clusters on two synthetic data sets: 3Gaussians and StripC. (A) The bar charts (in terms of ARI and NMI) of the five clustering methods on 3Gaussians. (B) The bar charts of the five clustering methods on StripC. (C) The ground truth and the clustering results of the five clustering methods on 3Gaussians. (D) The ground truth and the clustering results of the five clustering methods on StripC.