Fig. 5: scMerge2 is versatile to other single-cell platforms.
From: Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2
a UMAP plots of CyTOF data coloured by dataset (left) and cell type (right), for original (first row) and scMerge2 (second row). The red circles highlight the cell types (Neutrophils and Eosinophils) that are unique to Geanon (CyTOF). b Density plot of selected markers in specific cell types (CD4 in CD4 T cells), using original expression (first row) and scMerge2 adjusted expression (second row). Within a specific cell type, the distribution of the cell type markers are expected to be similar between two datasets. c Heatmaps indicate the clustering results and their fractions of concordance with the original cell type annotation given in ref. 29 for Original (first row) and scMerge2 (second row). Clearer diagonal structure illustrates better concordance. d Heatmaps indicate the average marker expression, calculated from cells aggregated by clusters for Original (first row) and scMerge2 (second row). More specific markers for each column and row indicates more distinguished clusters being identified. e Scatter plot indicates the average marker expression for each cluster, calculated using Original data (first row) and scMerge2 adjusted data (second row), for two pairs of protein markers: CD4 vs CD8 (first column); and CD4 vs CD20 (second column). Low concordance between the two markers is expected to reveal cluster with specific markers. f J-UMAP plot of integrated CITE-seq data coloured by dataset (left) and cell type (middle) and severity (right). Source data are provided as a Source Data file.
