Fig. 6: Single-cell deconvolution of mCAs.
From: Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution
a, Schematic overview of single-cell deconvolution of CH including mCAs and LOY by integrating SNP array and scRNA-seq data. b, Heatmaps showing in-sample ORs of each cell type containing cells with CNAs (left) and CN-LOHs (right). c, UMAP embedding of CH01 scRNA-seq data colored by three clones. d, Top ten enriched biological pathways of upregulated DEGs in monocytes of CH01 with 1p loss. Dot color indicates statistical significance of the enrichment (adjusted P values via the Benjamini–Hochberg method), and dot size represents the gene count assigned to each term. e, UMAP embedding of CH05 scRNA-seq data colored by two clones. f, Network plots showing the similarity of complementarity-determining region 3 (CDR3) amino acid sequences in BCR heavy and light chains of CH05 colored by clone (left) and isotype (right). Clonotype clusters with clonal size >1 are selected. g, Reactivity of antibodies against SARS-CoV-2 antigens (Ag) in enzyme-linked immunosorbent assays. Dots denote mean, and error bars show s.d. measured in triplicate. S309, anti-SARS-CoV-2 S immunoglobulin G (IgG)1; CH05, recombinant antibody derived from the CH05 BCR clonotype with 17q gain; nCoV396, anti-SARS-CoV-2 N IgG1; 23B12, anti-Candida albicans IgG1; OD450, optical density at 450 nm. Panel a created with BioRender.com.
