Journal: PLoS Computational Biology

Article Title: Scalable workflow for characterization of cell-cell communication in COVID-19 patients

doi: 10.1371/journal.pcbi.1010495

Figure Lengend Snippet: A. Heatmap of the pathway-specific cell-cell interaction (pCCI) contribution in monocytes as ligands and neutrophils as receptors in the Chua dataset, where the rows indicate the signaling pathways and columns indicate the samples. The signaling pathways are clustered into 6 groups. B. Dot plot indicating the cell-cell interaction contribution (pathway-cluster cell-cell interaction) in monocyte subgroups as ligands and neutrophils as receptors of the pathway-cluster 2 (upper panel) and pathway-cluster 4 (lower panel) as defined in (A). The columns indicate the 5 cellular subtypes of monocytes as ligands and the rows indicate the signaling pathways. A larger dot represents a higher level of cell-cell interaction. C. Bar plot indicating the log-ratio of cell-cell interaction contributions between two time points (y-axis) for longitudinal samples of 4 patients (2 moderate: BIH-CoV-12, BIH-CoV-15; 2 severe: BIH-CoV-06, BIH-CoV-07) in monocytes as ligands and neutrophils as receptors. The x-axis represents the signaling pathways. D. Heatmap of the cell-cell interaction contribution in monocytes as ligands and neutrophils as receptors for two patients (C143 and C146) in the Liao dataset that have more than 20 neutrophils, where the rows indicate the signaling pathways and columns indicate the samples. The signaling pathways are highlighted by the 6 signaling pathway clusters from (A).

Article Snippet: [B] Liao dataset—The raw count matrices of single-cell RNA-seq data from bronchoalveolar lavage fluid was downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) under the accession number GSE145926 .

Techniques: Protein-Protein interactions