Fig 1: SuPERR identifies significant cell-type misclassifications in other commonly-used approaches(A) Red points represent the peripheral blood mononuclear cells (PBMC) that were misclassified by either the conventional approach using GEX data only (i.e., Seurat v3), or by more recent approaches using both GEX and ADT data, such as the WNN in Seurat v4, and the SNF in CiteFuse. The Cell Fidelity Statistic (CFS, see STAR Methods) reports the fraction of correctly classified cells, the inverse of which is the fraction of misclassified cells (6.94% by Seurat v3, 5.16% by Seurat v4, 2.42% by CiteFuse).(B) Red points represent the bone marrow (BM) cells that were misclassified by Seurat v3 (5.31%), WNN/Seurat v4 (5.12%), and SNF/CiteFuse (5.15%) as determined by CFS. CFS scores show a progressive improvement in cell-type classification from Seurat v3 (GEX only) to Seurat v4 and CiteFuse, revealing higher agreement between CiteFuse and gold-standard biaxial gating of cell lineages.(C) The PBMC cluster 4 generated by the WNN method (Seurat v4) contains misclassified cells (i.e., a mixture of NK, NKT, and T cells) and was further explored using the cell-surface (ADT) markers CD56 and CD3 (left panel). The Differential Gene Expression (DGE) analysis for cluster 4 (pink circle) compared to “cleaned” NK cells (Venn diagram) shows the TRGV10 gene as a top hit. However, the TRGV10 gene is mostly expressed in CD3+ gamma-delta T cells and absent in NK cells (right panel). See also Figures S14–S17.