Latent feature extraction with a prior-based self-attention framework for spatial transcriptomics

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Figure 2.
Figure 2.

PAST effectively leverages reference data from various sources for spatial domain characterization. (A) Quantitative performance evaluation of spatial domain characterization on STARmap MPVC data set via supervised cross-validation and unsupervised spatial clustering with a specified number of clusters (Ncluster) and with default resolution (Dlouvain). The cross-validation performance was evaluated by the average score of Cohen's kappa value (κ) and mean F1 score (mF1), respectively, in the fivefold experiments. The spatial clustering performance was evaluated by adjusted rand index (ARI) and adjusted mutual information (AMI). (B) UMAP visualization results, (C) spatial visualization of clustering with a specified number of clusters and the manual annotation and (D) clustering evaluation of different methods under various dropout rates on MPVC data set.

This Article

  1. Published in Advance October 30, 2023, doi: 10.1101/gr.277891.123 Genome Res. 33: 1757-1773

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