Node reference

Visualization nodes.

The scRNA-seq plot nodes: embedding scatter (UMAP / t-SNE / PCA, coloured by metadata or a gene), PCA elbow and loadings, cluster composition and proportions, marker dotplots / heatmaps / violins / volcano, HVG dispersion, doublet diagnostics, trajectory and velocity overlays, pathway barplots and dotplots. Spatial, bulk, methylation, ATAC, CellRank and communication plots live in their own categories.

09 nodesCategory · vizin 15 templates

The parameters listed here are the plot-specific ones

Every plot node also opens into the Visualization Workspace, which adds the shared styling vocabulary — titles and font sizes, axes, legend placement, per-group colours, group renaming, export format and DPI — in the same five sections on every node. Those controls are documented once there rather than repeated on each card.

Embedding Plot

visualization

UMAP/t-SNE/PCA scatter colored by metadata or gene expression. After Scale, adata.X is z-scores — use layer="auto" or layer="normalized" for gene expression. highlight_expressing grays out non-expressing cells.

Node LibraryscRNA-seqSpatial

InAnnData (with embedding)

OutPNG image

Parameters (21)

Name	Type	Default	Description
`plot_type`	select	`umap`	umap/tsne/pca/scatter.
`color_by`	obs column	`leiden`	Comma-separated obs columns.
`gene_symbols`	array	—	Comma-separated genes for expression overlay.
`layer`	layer	`auto`	"auto" uses adata.raw if available.
`use_raw`	checkbox	`false`	Use adata.raw for expression values (overridden by layer='auto' logic).
`cmap`	select	`viridis`	Colormap.
`custom_cmap_low`	color	—	Custom colormap LOW endpoint (hex color, e.g. '#440154'). When both custom_cmap_low and custom_cmap_high are set, the cmap dropdown is overridden by a 2-color linear gradient from low → high.
`custom_cmap_high`	color	—	Custom colormap HIGH endpoint (hex color, e.g. '#fde725'). Paired with custom_cmap_low.
`publication_quality`	checkbox	`false`	Generate high-resolution (300 DPI) publication-quality figure.
`size`	number	`20`	Point size.
`figsize`	array	`[8, 6]`	Figure size [width, height] in inches.
`title`	text	—	Custom plot title. Empty = auto-generated from color_by.
`font_size`	number	—	Font size for all plot text (labels, legend, title). null = matplotlib default.
`vmin`	number	—	Minimum value for the color scale. null = data minimum (scanpy default).
`vmax`	number	—	Maximum value for the color scale. null = data maximum.
`highlight_expressing`	checkbox	`false`	Gray out expr=0 cells.
`frameon`	checkbox	`false`	Show axis frame around the embedding plot.
`ncols`	number	`4`	Subplots per row.
`wspace`	number	—	Width spacing between subplots when plotting multiple color_by values. null = renderer default.
`x`	text	`total_counts`	[scatter plot_type only] X-axis obs column.
`y`	text	`n_genes_by_counts`	[scatter plot_type only] Y-axis obs column.

PCA Visualization

pcaVisualization

PCA elbow (variance ratio), scatter, loadings, overview.

Node LibraryscRNA-seq

InAnnData (with PCA)

OutPNG image

Plots (4)variance_ratiopca_scatterloadingspca_overview

Parameters (9)

Name	Type	Default	Description
`plot_type`	text	`variance_ratio`	variance_ratio/pca_scatter/loadings/pca_overview.
`embedding`	text	`X_pca`	"X_pca" or "X_pca_harmony".
`n_pcs`	number	`30`	PCs to show in elbow.
`color_by`	text	—	Column to color PCA scatter by (obs key or gene name).
`n_genes`	number	`10`	Top genes in loadings.
`figsize`	array	`[12, 8]`	Figure size [width, height] in inches.
`cmap`	select	`viridis`	Colormap.
`font_size`	number	—	Font size for labels. null = matplotlib default.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

Cluster Visualization

clusterVisualization

Cluster composition, proportions, embedding overlay, dendrogram. IMPORTANT: "umap" is NOT a plot_type — it is an "embedding" param value. Use plot_type="embedding" + embedding="umap".

Node LibraryscRNA-seq

InAnnData (with clusters)

OutPNG image

Plots (5)compositionproportionsembeddingdendrogramcluster_overview

Parameters (7)

Name	Type	Default	Description
`plot_type`	text	`composition`	composition/proportions/embedding/dendrogram/cluster_overview.
`cluster_key`	text	`leiden`	Cluster column.
`groupby`	text	—	Secondary grouping for proportions.
`embedding`	select	`umap`	umap/tsne/pca.
`cmap`	text	`viridis`	Colormap for continuous plots.
`font_size`	number	—	Font size for labels. null = matplotlib default.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

Marker Visualization

markerVisualization

Heatmap, dotplot, violin, stacked violin, matrixplot, tracksplot, volcano of marker genes. Default is dotplot. Use custom_genes for known markers, or run findMarkers and use rank_genes_groups_dotplot.

Node LibraryscRNA-seq

InAnnData (with DEG results or custom genes)

OutPNG image

Plots (11)dotplotrank_genes_groups_dotplotheatmaprank_genes_groups_heatmapvolcanoviolinstacked_violinmatrixplotrank_genes_groups_matrixplottracksplotrank_genes_groups

Parameters (20)

Name	Type	Default	Description
`plot_type`	text	`dotplot`	11 plot types.
`n_genes`	number	`10`	Top genes per group.
`gene_source`	select	`DEG results`	Where the plotted genes come from. 'DEG results' = top-N ranked genes from findMarkers (requires rank_genes_groups). 'Manual gene list' = the comma-separated genes in custom_genes, no DEG run needed. Only heatmap/dotplot/matrixplot/violin/stacked_violin/tracksplot honour 'Manual gene list'; volcano and rank_genes_groups_* always use DEG.
`groupby`	text	—	Group column.
`groups`	text	—	Subset of groups to show. null = all groups. Pass list or 'all'.
`custom_genes`	text	—	Comma-separated gene names for a custom gene list (overrides the computed top-N genes for supported plot types).
`pval_threshold`	number	`0.05`	Volcano only: adjusted-p-value cutoff for significance.
`lfc_threshold`	number	`1.0`	Volcano only: absolute log-fold-change cutoff.
`n_top_labels`	number	`10`	Volcano only: number of top genes to label.
`symmetric_x`	checkbox	`false`	Volcano only: force symmetric log-fold-change axis limits around zero.
`highlight_genes`	text	—	Volcano only: comma-separated genes to highlight/label.
`gene_label_fontsize`	number	`8`	Volcano only: gene-label font size.
`figsize`	array	`[12, 8]`	Figure size [width, height] in inches. Ignored when figsize_auto is true.
`figsize_auto`	checkbox	`false`	Size the figure from the grid actually drawn (one column per gene, one row per group) instead of the fixed figsize. Applies to heatmap, rank_genes_groups_heatmap, dotplot and matrixplot.
`dendrogram`	checkbox	`true`	Show cluster dendrogram.
`layer`	layer	`auto`	"auto" uses adata.raw.
`use_raw`	checkbox	`true`	Use adata.raw.
`cmap`	select	`viridis`	Colormap for heatmap/dotplot.
`font_size`	number	—	Font size for labels. null = matplotlib default.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

HVG Visualization

hvgVisualization

Highly variable gene dispersion plot.

Node LibraryscRNA-seq

InAnnData (with HVG)

OutPNG image

Parameters (11)

Name	Type	Default	Description
`log`	checkbox	`true`	Log scale axes.
`n_top_genes`	number	`15`	Top HVGs to label.
`show_text`	checkbox	`true`	Show gene name labels.
`hvg_color`	color	`black`	Point colour for the selected highly-variable genes. Any matplotlib colour ('black', '#1f77b4'). Blank = the default.
`non_hvg_color`	color	`grey`	Point colour for the non-selected genes. Any matplotlib colour. Blank = the default.
`highlight_genes`	text	—	Comma-separated gene names to ring and label regardless of rank. Use this instead of raising n_top_genes when you care about specific genes.
`show_cutoff_lines`	checkbox	`false`	Draw dotted guides at the mean/dispersion boundary of the selected HVG set.
`figsize`	array	`[10, 4]`	Figure size [width, height] in inches.
`title`	text	—	Custom plot title.
`font_size`	number	—	Font size. null = matplotlib default.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

Doublet Visualization

doubletVisualization

Histogram, scatter, embedding overlay of doublet detection results.

Node LibraryscRNA-seq

InAnnData (with doublet detection)

OutPNG image

Plots (3)histogramscatteroverview

Parameters (8)

Name	Type	Default	Description
`plot_type`	text	`histogram`	histogram/scatter/embedding/overview.
`show_threshold`	checkbox	`true`	Show threshold line.
`threshold`	number	—	Optional threshold override. null = use adata.uns['scrublet']['threshold'] when available.
`n_bins`	number	`50`	Histogram bin count for histogram/overview.
`figsize`	array	`[12, 5]`	Figure size [width, height] in inches.
`title`	text	—	Custom plot title.
`font_size`	number	—	Font size. null = matplotlib default.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

Trajectory Visualization

trajectoryVisualization

PAGA graph, DPT pseudotime, diffusion map, draw_graph plots.

Node LibraryscRNA-seq

InAnnData (with trajectory)

OutPNG image

Plots (6)pagapaga_embeddingdpt_pseudotimedpt_groupsdiffmapdraw_graph

Parameters (11)

Name	Type	Default	Description
`plot_type`	text	`paga`	paga/paga_embedding/dpt_pseudotime/dpt_groups/diffmap/draw_graph.
`groups`	text	`leiden`	Cluster column.
`embedding`	select	`umap`	Embedding for overlay.
`threshold`	number	`0.01`	PAGA edge threshold.
`node_size_scale`	number	`1.0`	Scale factor for PAGA node sizes.
`edge_width_scale`	number	`1.0`	Scale factor for PAGA edge widths.
`color_by`	text	—	Column to color embedding by.
`cmap`	select	`viridis`	Colormap.
`font_size`	number	—	Font size. null = matplotlib default.
`title`	text	—	Custom plot title.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

Velocity Visualization

velocityVisualization

Stream, arrow, phase portrait, speed, coherence, latent time.

Node LibraryscRNA-seq

InAnnData (with velocity + velocity graph)

OutPNG image

Plots (8)streamgridarrowphase_portraitspeedcoherencelatent_timevelocity_overview

Parameters (15)

Name	Type	Default	Description
`plot_type`	text	`stream`	7 plot types incl. velocity_overview.
`basis`	text	`umap`	Embedding.
`color_by`	text	—	Column to color by.
`gene`	text	—	Gene for phase portrait.
`density`	number	—	Stream/arrow density.
`smooth`	number	—	Stream/grid smoothing factor. null = scVelo default.
`min_mass`	number	—	Minimum arrow mass threshold. null = scVelo default.
`arrow_length`	number	—	Arrow length scale for grid/arrow plots. null = scVelo default; stream ignores this parameter.
`arrow_size`	number	—	Arrow size.
`size`	number	—	Point size. null = scVelo default.
`alpha`	number	—	Point transparency. null = scVelo default.
`cmap`	select	`viridis`	Colormap.
`font_size`	number	—	Font size. null = matplotlib default.
`title`	text	—	Custom plot title.
`publication_quality`	checkbox	`false`	Generate high-resolution publication-quality figure.

Pathway Visualization

pathwayVisualization

Enrichr GO/KEGG enrichment as barplot or dotplot.

Node LibraryscRNA-seq

InAnnData (with pathway_enrichment)

OutPNG image

Plots (2)barplotdotplot

Parameters (6)

Name	Type	Default	Description
`plot_type`	text	`barplot`	"barplot" or "dotplot".
`gene_set`	text	—	Database to plot (auto if empty).
`n_top_terms`	number	`5`	Top terms per cluster.
`clusters`	text	—	Specific clusters (empty = all).
`figsize_w`	number	`14`	Figure width in inches.
`figsize_h`	number	`12`	Figure height in inches. Increase for many clusters.

Cell-Cell Communication

Spatial