Visualization Gallery

Introduction

NOVA provides a comprehensive suite of visualization functions to explore and present cell-cell communication analysis results. This gallery demonstrates the various plotting capabilities with practical examples.

Setup

library(NOVA)
library(ggplot2)

Creating Example Data

set.seed(123)

# Simulate expression matrix
n_genes <- 200
n_cells <- 500
gene_names <- paste0("Gene", 1:n_genes)
cell_names <- paste0("Cell", 1:n_cells)

expr <- matrix(0, nrow = n_genes, ncol = n_cells,
               dimnames = list(gene_names, cell_names))
expressed <- sample(length(expr), size = length(expr) * 0.25)
expr[expressed] <- abs(rnorm(length(expressed), mean = 3, sd = 1.5))
expr <- Matrix::Matrix(expr, sparse = TRUE)

# Create clusters
clusters <- sample(c("T_cells", "B_cells", "Macrophages", "Fibroblasts", "Dendritic"), 
                   n_cells, replace = TRUE, prob = c(0.25, 0.20, 0.25, 0.15, 0.15))
names(clusters) <- cell_names
annotation <- data.frame(cell = cell_names, cluster = clusters)

# Map genes to LR database
lr_db <- GetLRDatabase("lrc2p")
ligands <- unique(lr_db$ligand)[1:30]
receptors <- unique(lr_db$receptor)[1:30]
rownames(expr)[1:30] <- ligands
rownames(expr)[31:60] <- receptors

Running Analysis

# Run NOVA analysis
result <- ExtractEdges(
  expression = expr,
  annotation = annotation,
  species = "human",
  database = "lrc2p",
  min_pct = 0.05
)

print(result)

1. Communication Heatmap

The heatmap displays the overall communication strength between cell types.

Basic Heatmap

# Count-based heatmap
ht <- PlotHeatmap(result, metric = "count", show_values = TRUE)

Specificity-weighted Heatmap

# Specificity-based heatmap
ht_spec <- PlotHeatmap(result, metric = "specificity", show_values = TRUE)

2. Network Visualization

Network graphs provide an intuitive view of communication patterns.

Circular Layout

PlotNetwork(result, 
            layout = "circle",
            metric = "count",
            title = "Cell-Cell Communication Network")

Force-directed Layout

PlotNetwork(result, 
            layout = "fr",  # Fruchterman-Reingold
            metric = "specificity",
            title = "Communication Network (FR Layout)")

Kamada-Kawai Layout

PlotNetwork(result, 
            layout = "kk",
            metric = "count",
            title = "Communication Network (KK Layout)")

3. Chord Diagram

Chord diagrams elegantly display the flow of communication between cell types.

PlotChord(result, 
          metric = "count",
          transparency = 0.4,
          title = "Communication Flow")

Specificity-based Chord

PlotChord(result, 
          metric = "specificity",
          transparency = 0.5,
          title = "Specificity-weighted Communication")

4. Ligand-Receptor Pairs Visualization

Examine specific LR pairs between cluster pairs.

# Get specific cluster pair interactions
PlotLRPairs(result, 
            sending = "T_cells", 
            target = "Macrophages",
            top_n = 15,
            rank_by = "specificity",
            title = "T cells → Macrophages LR Interactions")
PlotLRPairs(result, 
            sending = "Macrophages", 
            target = "Fibroblasts",
            top_n = 10,
            rank_by = "mean")

5. Color Palette

NOVA provides a custom color palette optimized for cell type visualization.

# Display color palette
colors <- nova_palette(20)
barplot(rep(1, 20), col = colors, border = NA, axes = FALSE,
        main = "NOVA Color Palette")
NOVA color palette

NOVA color palette

6. Custom Styling

Custom Colors

custom_cols <- c("T_cells" = "#E64B35", 
                 "B_cells" = "#4DBBD5", 
                 "Macrophages" = "#00A087",
                 "Fibroblasts" = "#3C5488",
                 "Dendritic" = "#F39B7F")

PlotNetwork(result, 
            layout = "circle",
            colors = custom_cols,
            title = "Network with Custom Colors")

7. Saving Plots

# Save heatmap to PDF
SavePlot(ht, "communication_heatmap.pdf", width = 10, height = 8)

# Save network to PNG
p <- PlotNetwork(result, layout = "circle")
SavePlot(p, "communication_network.png", width = 10, height = 8, dpi = 300)

Summary Table

Function Description Output Type
PlotHeatmap() Communication strength heatmap ComplexHeatmap
PlotNetwork() Network graph ggplot2
PlotChord() Chord diagram Base R
PlotLRPairs() Bipartite LR visualization ggplot2
PlotDiffHeatmap() Differential communication heatmap ComplexHeatmap
PlotVolcano() Volcano plot ggplot2

Session Info

sessionInfo()
#> R version 4.6.0 (2026-04-24)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.4 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] ggplot2_4.0.3     data.table_1.18.4 NOVA_1.0.0        rmarkdown_2.31   
#> 
#> loaded via a namespace (and not attached):
#>  [1] Matrix_1.7-5       gtable_0.3.6       jsonlite_2.0.0     dplyr_1.2.1       
#>  [5] compiler_4.6.0     tidyselect_1.2.1   Rcpp_1.1.1-1.1     parallel_4.6.0    
#>  [9] jquerylib_0.1.4    scales_1.4.0       yaml_2.3.12        fastmap_1.2.0     
#> [13] lattice_0.22-9     R6_2.6.1           generics_0.1.4     knitr_1.51        
#> [17] tibble_3.3.1       maketools_1.3.2    bslib_0.11.0       pillar_1.11.1     
#> [21] RColorBrewer_1.1-3 rlang_1.2.0        cachem_1.1.0       xfun_0.57         
#> [25] sass_0.4.10        sys_3.4.3          S7_0.2.2           otel_0.2.0        
#> [29] cli_3.6.6          withr_3.0.2        magrittr_2.0.5     digest_0.6.39     
#> [33] grid_4.6.0         lifecycle_1.0.5    vctrs_0.7.3        evaluate_1.0.5    
#> [37] glue_1.8.1         farver_2.1.2       buildtools_1.0.0   tools_4.6.0       
#> [41] pkgconfig_2.0.3    htmltools_0.5.9

Author

Zaoqu Liu