Documentation/Nodes/Visualization

Visualization Nodes

Comprehensive visualization tools including 20+ plot types, interactive molecular viewers, and publication-ready scientific charts for data analysis and presentation.

Available Plot Categories

Statistical Plots

Basic statistical visualizations

HistogramScatterLineBarBoxViolinKDEECDF

Scientific Plots

Specialized scientific visualizations

VolcanoVennHeatmapPair PlotRadarBubble

3D Plots

Three-dimensional visualizations

3D Scatter3D Surface3D Line

Molecular Viewers

Chemical structure visualization

2D Structure3D ViewerInteraction Maps

Node Reference

Detailed documentation for visualization and plotting nodes in VERA.

Structure Draw 2D

Generate 2D molecular structure depictions using RDKit

Type: structure_draw_2dCategory: Molecular Visualization

Key Features

•High-quality 2D depictions
•Atom/bond highlighting
•Grid layout for multiple molecules
•SVG vector output
•Customizable drawing options

Input Ports

moleculesmolecules

RDKit molecule objects to draw

highlight_atomsdata

Optional atom indices to highlight

Output Ports

imagesimage

2D structure images

grid_imageimage

Grid of multiple structures

svg_datastring

SVG representation

Properties

Property	Type	Default	Description
img_size	tuple	(300, 300)	Image dimensions (width, height)
mol_per_row	int	3	Molecules per row in grid
show_atom_numbers	bool	false	Display atom indices
highlight_color	string	yellow	Highlight color
kekulize	bool	true	Use Kekulé form

ProLIF Interaction

Protein-ligand interaction fingerprinting and analysis

Type: prolif_interactionCategory: Molecular Visualization

Key Features

•Hydrogen bonds detection
•Hydrophobic interactions
•π-π stacking analysis
•Salt bridges identification
•Interactive visualizations

Input Ports

protein_moleculesmolecules

Protein structure

ligand_moleculesmolecules

Ligand molecules

trajectory_filefile

Optional MD trajectory

Output Ports

interaction_datadata

Interaction fingerprint DataFrame

interaction_plotimage

Interaction heatmap

network_plotimage

Interaction network diagram

barcode_plotimage

Interaction barcode

Properties

Property	Type	Default	Description
interactions	string	all	Interaction types to detect
distance_cutoff	float	4.5	Distance cutoff (Å)
residue_selection	string	all	Residues to analyze
plot_type	string	heatmap	Visualization type

Web 3D Viewer

Interactive 3D molecular viewer using NGL.js

Type: web3d_viewerCategory: Molecular Visualization

Key Features

•Interactive 3D rotation/zoom
•Multiple representation styles
•Trajectory playback
•Measurement tools
•Export as HTML

Input Ports

moleculesmolecules

Molecular structures

trajectory_filefile

Optional trajectory

structure_filefile

Or structure file (PDB/SDF)

Output Ports

viewer_htmlfile

Standalone HTML viewer

viewer_urlstring

Viewer URL

screenshotimage

Static screenshot

Properties

Property	Type	Default	Description
representation	string	cartoon	Display style (cartoon, ball+stick, surface)
color_scheme	string	chainid	Coloring (element, chain, residue)
background	string	white	Background color
show_axes	bool	false	Show orientation axes
auto_view	bool	true	Auto-center view

Histogram Plot

Create histogram distributions with statistical overlays

Type: plot_histogramCategory: Statistical Plots

Key Features

•Automatic bin optimization
•KDE overlay option
•Statistical annotations
•Multiple histograms
•Interactive plotly output

Input Ports

datadata

Data values (DataFrame or array)

column_namestring

Optional column to plot

Output Ports

plotimage

Histogram plot

statisticsdata

Distribution statistics

bins_datadata

Bin edges and counts

Properties

Property	Type	Default	Description
bins	int	auto	Number of bins
density	bool	false	Normalize to density
cumulative	bool	false	Cumulative histogram
overlay	string	none	Overlay (kde, normal)
color	string	blue	Bar color

Scatter Plot

2D/3D scatter plots with regression lines

Type: plot_scatterCategory: Statistical Plots

Key Features

•2D and 3D scatter plots
•Color/size mapping
•Regression lines
•Confidence intervals
•Interactive hover data

Input Ports

datadata

DataFrame with x, y columns

x_datadata

Or separate x values

y_datadata

And y values

z_datadata

Optional z for 3D

Output Ports

plotimage

Scatter plot

regression_statsdata

Regression statistics

correlationdata

Correlation coefficient

Properties

Property	Type	Default	Description
x_column	string		X axis column
y_column	string		Y axis column
color_column	string		Color by column
size_column	string		Size by column
trendline	string	none	Trendline type (linear, lowess)
marker_size	int	8	Marker size

Line Plot

Time series and line charts with multiple traces

Type: plot_lineCategory: Statistical Plots

Key Features

•Multiple traces
•Time series support
•Area fills
•Smooth interpolation
•Dual y-axes

Input Ports

datadata

DataFrame or arrays

x_datadata

X axis values

y_datadata

Y axis values

Output Ports

plotimage

Line plot

plot_datadata

Plot data export

Properties

Property	Type	Default	Description
x_column	string		X axis column
y_columns	string		Y columns (comma-separated)
line_style	string	solid	Line style
markers	bool	false	Show markers
fill	string	none	Fill area (tozeroy, tonexty)

Bar Plot

Bar charts with grouping and stacking

Type: plot_barCategory: Statistical Plots

Key Features

•Grouped bars
•Stacked bars
•Horizontal/vertical
•Error bars
•Annotations

Input Ports

datadata

DataFrame with categories and values

categoriesdata

Category labels

valuesdata

Bar heights

Output Ports

plotimage

Bar plot

summary_statsdata

Summary statistics

Properties

Property	Type	Default	Description
orientation	string	vertical	Bar orientation
bar_mode	string	group	Mode (group, stack, overlay)
color_discrete_map	string		Color mapping
show_values	bool	true	Show value labels

Heatmap Plot

2D heatmaps with hierarchical clustering

Type: plot_heatmapCategory: Statistical Plots

Key Features

•Hierarchical clustering
•Custom color scales
•Dendrograms
•Cell annotations
•Interactive zoom

Input Ports

datadata

2D matrix or DataFrame

row_labelsdata

Optional row labels

col_labelsdata

Optional column labels

Output Ports

plotimage

Heatmap plot

clustered_datadata

Clustered matrix

dendrogramimage

Optional dendrogram

Properties

Property	Type	Default	Description
colorscale	string	viridis	Color scale
cluster_rows	bool	false	Cluster rows
cluster_cols	bool	false	Cluster columns
show_scale	bool	true	Show color scale
annotate	bool	false	Show cell values

Pie/Donut Plot

Pie and donut charts for proportional data

Type: plot_pieCategory: Statistical Plots

Key Features

•Pie and donut styles
•Percentage labels
•Exploded slices
•Custom colors
•Interactive legends

Input Ports

datadata

Categories and values

labelsdata

Category labels

valuesdata

Category values

Output Ports

plotimage

Pie/donut chart

percentagesdata

Percentage breakdown

Properties

Property	Type	Default	Description
hole	float	0	Hole size (0 for pie, >0 for donut)
textposition	string	auto	Label position
textinfo	string	percent+label	Text display
pull	float	0	Explode slices

Box Plot

Box plots showing quartiles and outliers

Type: plot_boxCategory: Statistical Plots

Key Features

•Quartile visualization
•Outlier detection
•Group comparisons
•Mean overlay
•Confidence intervals

Input Ports

datadata

Data values or DataFrame

groupsdata

Optional grouping variable

Output Ports

plotimage

Box plot

statisticsdata

Quartile statistics

outliersdata

Outlier points

Properties

Property	Type	Default	Description
orientation	string	vertical	Plot orientation
notched	bool	false	Show confidence notch
show_mean	bool	false	Show mean line
points	string	outliers	Point display (all, outliers, none)

Violin Plot

Violin plots combining KDE and box plots

Type: plot_violinCategory: Statistical Plots

Key Features

•Distribution shape
•Embedded box plot
•KDE smoothing
•Split violins
•Statistical overlays

Input Ports

datadata

Data values

groupsdata

Grouping variable

Output Ports

plotimage

Violin plot

kde_datadata

KDE curves

statisticsdata

Distribution stats

Properties

Property	Type	Default	Description
box_visible	bool	true	Show box plot inside
meanline_visible	bool	false	Show mean line
points	string	none	Show data points
bandwidth	float	auto	KDE bandwidth

Volcano Plot

Volcano plots for differential expression analysis

Type: plot_volcanoCategory: Scientific Plots

Key Features

•Significance thresholds
•Auto-labeling
•Color by significance
•Interactive tooltips
•Export significant list

Input Ports

datadata

DataFrame with fold change and p-values

fold_changedata

Or separate fold change

pvaluesdata

And p-values

Output Ports

plotimage

Volcano plot

significant_genesdata

Significant features

statisticsdata

Statistical summary

Properties

Property	Type	Default	Description
fc_threshold	float	2.0	Fold change cutoff
pvalue_threshold	float	0.05	P-value cutoff
log_transform	bool	true	Log transform FC
label_top	int	10	Label top N points

Venn Diagram

Venn diagrams for set intersections (2-3 sets)

Type: plot_vennCategory: Scientific Plots

Key Features

•2 and 3 set diagrams
•Proportional sizing
•Intersection counts
•Custom colors
•Export intersections

Input Ports

set1data

First set of items

set2data

Second set

set3data

Optional third set

Output Ports

plotimage

Venn diagram

intersectionsdata

Intersection counts

unique_itemsdata

Unique items per region

Properties

Property	Type	Default	Description
set_labels	string	Set1,Set2,Set3	Set names
colors	string	red,blue,green	Set colors
alpha	float	0.4	Transparency
show_percentages	bool	false	Show percentages

Pair Plot

Matrix of scatter plots for multi-dimensional data

Type: plot_pairplotCategory: Scientific Plots

Key Features

•All pairwise relationships
•Diagonal distributions
•Group coloring
•Regression lines
•Correlation annotations

Input Ports

datadata

Multi-column DataFrame

hue_columnstring

Optional grouping column

Output Ports

plotimage

Pair plot matrix

correlationsdata

Correlation matrix

regression_statsdata

Pairwise regressions

Properties

Property	Type	Default	Description
diag_kind	string	hist	Diagonal plot type (hist, kde)
plot_kind	string	scatter	Off-diagonal plots (scatter, reg)
height	float	2.5	Subplot height
corner	bool	false	Show lower triangle only

Radar Plot

Radar/spider charts for multivariate comparison

Type: plot_radarCategory: Scientific Plots

Key Features

•Multi-dimensional comparison
•Multiple traces
•Area filling
•Custom scaling
•Interactive legends

Input Ports

datadata

DataFrame with variables

categoriesdata

Variable names

valuesdata

Variable values

Output Ports

plotimage

Radar chart

normalized_datadata

Normalized values

Properties

Property	Type	Default	Description
fill	bool	true	Fill area
normalize	bool	true	Normalize to 0-1
show_grid	bool	true	Show grid lines
line_width	int	2	Line thickness

Visualization Best Practices

Choose the right plot type: Use histograms for distributions, scatter for correlations, line for time series, and heatmaps for matrices.
Interactive vs Static: Plotly outputs are interactive and great for exploration, while static images are better for publications.
Molecular visualization: Use 2D for structure comparison, 3D viewer for spatial analysis, and ProLIF for interaction studies.
Publication quality: Adjust DPI, font sizes, and color schemes for journal requirements. Export as vector graphics when possible.