Table 1.

List of modules implemented in VDJView with their outputs and integrated packages

Module	Description	Software packages	Output
Filtering	Selection of cells based on metadata, gene and immune receptor features	dplyr	Venn Diagram, data-table
Quality control	Metrics with options for easily filtering cells according to total read counts, number of genes, and percentage of mitochondrial/ribosomal genes	Seurat [11]	Violin plots
Random sampling	Selection of small subsets of data, providing the ability to analyse larger datasets	Seurat
Clonotype usage	Pie charts of single- and paired-chain CDR3 contig usage for both T and B cells. Tables detailing single- and paired-chain CDR3 contigs generated across all cells	plotly	Pie charts, data-tables
CDR3 length	Distribution of CDR3 lengths for single- and paired chains	tcR	Histograms
VDJ gene usage	Distribution of V, D and J gene usage for single chains	tcR	Histograms
Gene interactions	Frequencies of inter- and intra-chain VDJ gene pairings, and inter-chain CDR3 pairings	Rcircos [12]	Circos plots
Shared clonotypes	Table and scatter plot detailing the number of single- and paired-chain CDR3 contigs and VDJ genes that occur in multiple subgroups, and their frequency in each group	tcR	Scatter plot, data-table
Dimensionality reduction	PCA plot, t-SNE plot and UMAP plot with customisable parameters. Metadata can be used to control data point shape, size and colour. Data points are selectable and displayed with their metadata in a data-table below each plot	Scater [13], Seurat, SC3 [14]	PCA plots, t-SNE plots, UMAP plots, data-tables
Unsupervised clustering	Consensus matrix, gene expression heatmaps and marker-gene heatmaps are calculated by SC3 based on user defined cluster ranges, p-values and AUROC values. Metadata can be displayed above plot. Gene list can be uploaded to generate an expression heatmap. Tabular SC3 clustering information is generated	Scater, SC3	Consensus matrix, Expression matrix, DE Genes heatmap, Marker genes heatmap, data-table
Supervised clustering	Differentially expressed gene heatmap generated by MAST comparing groups of cells based on clusters predetermined by the user, p-value and fold change thresholds. Gene fold change values and a tabular version of the heatmap are generated	MAST [15], Scater, pheatmap	Gene expression matrix, data-tables
Pseudo-time	Pseudo-time plot to determine single-cell state trajectories based on genes which are differentially expressed between user defined metadata groups	Monocle [16]	Pseudo-time cell trajectory plot
Cell metadata summary	Tabular summary of the cells uploaded, the metadata associated with them and the number of receptors contigs, and expressed genes reported for each cell		Data-table