Fig. 5: TAS-Seq identifies more cell–cell interactions than 10X v2 and Smart-seq2 in murine lung tissue.
From: TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq
a Changes of the number of inferred interactions/pathways of cell–cell interaction network of each scRNA-seq dataset of murine lung predicted by CellChat when the threshold of genes of which minimum fraction of expressed cells within each cell subset. Error bars show mean ± SD in TAS-Seq.shallow and TAS-Seq.deep samples. b Scatter plot of incoming (target) and outgoing (source) signaling strength within the cell–cell interaction network of each cell subset (minimum expression of genes in each cell subset ≥ 0.15). Dot size represents the sum of incoming and outgoing signals in each cell subset. Capillary endothelial cells, alveolar type 2 cells, and alveolar fibroblasts were strongly connected in the TAS-Seq and Smart-seq2 dataset networks, and cell subsets were more strongly connected in the TAS-Seq dataset than in the Smart-seq2 dataset. The overall connections were weak in 10X v2 datasets. c Circle plot visualizations of cell–cell interaction network of each scRNA-seq dataset of murine lung within particular cell subsets. Circle sizes represent the cell number of each subset. Wider edge means stronger communication, and edge width was normalized among all datasets. See also Supplementary Fig. 12b for the cell–cell interaction network of all cell subsets. Abbreviations of cell subsets were shown in Supplementary Data 6.
