Additional file 1 of eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells
Creators: name: Mori, Tomoya
name: Takase, Toshiro
name: Lan, Kuan-Chun
name: Yamane, Junko
name: Alev, Cantas
name: Kimura, Azuma
name: Osafune, Kenji
name: Yamashita, Jun K.
name: Akutsu, Tatsuya
name: Kitano, Hiroaki
name: Fujibuchi, Wataru
Publisher: name: figshare
Year: 2023
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1 Fig. S1. GO mapping of SDGs in Biological Process for mouse E7.0 gastrula embryo. The p-values determined on the basis of hypergeometric distribution statistics are shown on top of bars. Fig. S2. Topology graphs for 12 datasets used as input for eSPRESSO clustering in this study. Fig. S3. Gene expression gradients in reconstructed models by eSPRESSO (upper) and novoSpaRc (lower) for the top three important genes in VKO analysis of mouse developmental heart. Fig. S4. Gene expression gradients in reconstructed models by eSPRESSO (upper) and novoSpaRc (lower) for the top three important genes in VKO analysis of the human developmental pancreas. Fig. S5. GGM raw result by glasso for original 18 cell types at individual stages (left) and induced developmental model by reduced 10 cell types (right). Fig. S6. Venn diagrams representing consensus S(T)DGs identified by eSPRESSO and cluster biomarkers identified by Seurat, and enrichment plots of the S(T)DGs for the gene lists ranked according to the adjusted p-values obtained by the Wilcoxon rank sum test between one domain and the other domains. P.adj and NES denote adjusted p-value and normalized enrichment score, respectively. Fig. S7 Synthetic single-cell dataset created from a dyngen model with linear backbone of transcription factor module configuration, and a topology graph generated from the dataset. a Module network of linear backbone generated by dyngen. b Transcription factor and target gene regulatory network generated by dyngen. c UMAP of 1,000 cells of the synthetic dataset. Numbers in the legend are the cluster numbers identified by the Louvain method. d Topology graph generated from the synthetic dataset. Vertex labels indicate domain names corresponding to the cluster numbers in (c). Fig. S8. Topology graphs generated from synthetic single-cell datasets of predefined 14 backbones by dyngen. The dyngen parameters for generating each dataset are indicated by Seed, random seed; #TF, the number of transcription factors; #Targets, the number of target genes; and #HK, the number of housekeeping genes. Thresholds indicate the cut-off values for generating topology graphs from the correlation networks of identified domains. Fig. S9 Expression gradients of SDGs identified by eSPRESSO on topology graphs generated from the synthetic datasets. Vertex colors indicate gene expression levels (Z-score) of the cluster centroids. Fig. S10. Impact of misspecification of input topology. Each plot shows the mean values of maximum scores (= accuracy + ARI), maximum accuracies, and maximum ARIs, respectively, and 95% confidence intervals for ten experiments with increasing randomization probability. Fig. S11. Venn diagrams representing input genes to Boruta selected on the basis of the frequency of nonzero expression in all cells as well as the standard deviation (eSPRESSO) and highly variable genes by Seurat (Seurat).