Table 1 List of modules implemented in VDJView with their outputs and integrated packages

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