Extended Data Fig. 2: Refined B cell subpopulations discovered by CellLENS in a tonsil CODEX dataset.

(A) Metrics evaluation of clustering performances on CODEX human tonsil tissue. Embeddings/representations of cells, from 7 different methods, were used as input: CellSNP representation, feature (protein expression table), concact (protein expression + neighborhood composition table), CCA representation, MOFA+ representation, SpiceMix representation, and MUSE representation. Clusters (for the calculation of Silhouette score, CH, and DB index) were generated with Leiden clustering using the same parameters. (B) UMAP visualization of the embedding and Leiden clustering result (cc: CellLENS clusters; fc; feature-only clusters). Left panel: CellLENS embedding; Right panel: feature expression table. (C) Zoom-in of the UMAP visualization of B cells (green), germinal center B cells (purple), and replicating non-GC cells (red) on CellLENS embedding (left) and feature-only embedding (right). Cells colored according to cell populations identified using CellLENS clusters in both UMAPs. (D) Zoom-in of the UMAP visualization of the same cell types shown in C, but colored by cluster numbers from CellLENS embedding (left) and feature-only embedding (right). CellLENS successfully separated replicating non-GC cells from GC B cells (c10 and c8), where feature-only failed (c8 partial). (E) B cell and replication-related marker expression (z-normed) heatmap. Left panel: clusters from CellLENS; Right panel: clusters from feature-only. (F) Visualization of cell type locations: B cells (green), GC B cells (purple), and replicating non-GC cells (red). Based on the location, replicating non-GC cells should not be mixed with GC B cells, as shown in the clustering result from feature-only.