chromoMap2

HOW IT WORKS

Create a chromoMap Plot in three steps

Data

Enter input data using one of the options provided below.

chromoMap2 Features

Visualise feature-associated numerical or categorical data as heatmaps, bar, scatter, line, and other plots. Start in Visualise Data, configure the map in Plot Properties, and explore special plot features in Additional Features.

Create chromoMaps

Build the configured map using the Create chromoMap button in the status bar below.

Project nameSaved projects

Visualise data

Visualize omics data on genomic coordinates for each chromosome set.

Options are applied per chromosome set

Use the selector below to choose the set whose visualization you want to edit.

Chromosome set to edit

Data to visualise

Choose one data mode for the selected chromosome set.

Annotations onlyCategoricalNumeric

Heat map

Visualise the selected annotation data as a chromosome heatmap. For color and domain configuration, go to Plot Properties.

Show heat map

Plot type

Available plot types change with the numerical or categorical data selection above.

Plot properties

Configure chromosome geometry, positioning, scales, and text.

Plot title and description

Describe the values, units and context to retain with the saved plot.

TitleScientific description

Chromosome layout

Control the primary plot geometry and spacing.

Chromosome widthVisual window width (px)Corner curveChromosome gapChromosome-set gapTop marginLeft marginMargin paddingText x-shift

Automatic left marginCenter plotWindow guides

Guide color

Genomic scale

Format coordinate axes. Tick density adjusts automatically to the available width.

Scale modeMajor ticksMinor ticksScale suffixY scale offset

Typography

Set text sizes used throughout the map.

Chromosome text sizeTitle font sizeAxis font sizeLegend font sizeTooltip font size

Plot y-axis label config

Position and size labels beside numeric plots.

Y-label x offsetY-label y offsetY-label size

Legend positioning

Position global plot legends and chromoLinks legends.

Links legend xLinks legend yPlot legend xPlot legend yLegend position

Per-set properties

Changes below affect only the selected chromosome set.

Chromosome set to edit

Numeric domain

Choose whether numeric limits are calculated together or per chromosome set.

Numeric domain scope

Additional features

Fine-tune resolution and add genomic context.

Map resolution

Choose adaptive or fixed genomic windows.

Adaptive windowsFixed size

Window factorWindow size (bp)

Remove partial last windowShow window summariesMap spanning annotations

Plot highlights

Shade selected genomic regions behind or above the map.

Highlights JSON array

Import highlights CSV/TSVHighlight layer

Labelling

Display all annotation names or a selected subset.

Annotation labelsOnly label these names comma-separated; blank = all

Max labels/windowLabel fontAngleLabel separator

Strand arrows

Show annotation direction using strand-aware arrows.

Enable strand arrows

Arrow placementArrow colorArrow sizeArrow tail

Markers

Place markers above selected annotations.

Feature names comma-separated

SizeY offsetStroke

Add Text

Add publication-ready custom text directly to the plot SVG. Drag it on the plot to reposition it; the text is included in PNG and SVG exports.

TextFontColorSizeRotation

Italic textUnderline text

Custom legends

Add independent categorical or numeric legends. These legends are global and are not tied to a chromosome set.

Statistical analysis

Compare numeric or categorical series across exactly matched genomic windows.

ComparisonsTestsSignificance thresholdMultiple-testing correction

Create chromoMap first. The analysis uses the active aggregation for each series. Paired t-tests assume independent, approximately normal paired differences; genomic windows are not biological replicates. Use measurements with compatible units for a paired t-test.

How to read statistical results

Start with the adjusted p-value. Below the selected threshold (0.05 or 0.01) is labelled statistically significant for this run. This is evidence against the test’s no-difference or no-association assumption, under its statistical model; it does not prove a hypothesis true. At or above that threshold, the test has not found sufficient evidence—it does not prove the series are identical or unrelated.

Paired t-test: asks whether the mean paired difference is zero. Positive Δ means the first series is higher on average; negative Δ means lower. The 95% confidence interval describes uncertainty in Δ and is not adjusted for multiple testing.
Pearson correlation: asks whether linear correlation is zero. Positive r means values tend to increase together; negative r means they tend to move in opposite directions. Values nearer −1 or +1 indicate stronger linear association; values near zero indicate weak linear association. Correlation does not show causation.
Chi-square: asks whether category membership is independent. A significant result supports an association; Cramér’s V describes its strength from 0 to 1, not a positive or negative direction. Numeric measurements are binned into quartiles for numeric/category comparisons.

Matched n counts paired genomic windows. A dash means the test value is unavailable; read the checks for its reason. Statistical significance does not measure effect size or biological importance.

chromoLinks

Connect annotations and loci across chromosomes or chromosome sets.

Link data

Paste JSON, import a CSV/TSV table, or build links from the annotations already loaded.

Loci links JSON array

Import loci links CSV/TSV

Link appearance

Configure shape, direction, and color mapping.

Show linksDirected linksColor map

Export

Download the current plot, an editable HTML project, or its window-level data.

Plot image

These actions use chromoMap2’s built-in export engine.

File namePNG scale

Standalone HTML plot

Export an interactive HTML figure containing the data and configuration. Choose online libraries for a single-file download, or local libraries for offline viewing.

Choose how the HTML will openWith internet: select Online libraries and download just the HTML. Without internet: select Local libraries and download the HTML plus d3.v5.js and chromoMap2.js using the buttons below. Keep all three files together in the same folder.

HTML dependency modeDownload d3.v5.js Download chromoMap2.js

Window data

Export computed chromosome-window summaries as CSV.

Generate a plot firstExport actions become available after chromoMap2 renders.

Generated code

Copy the current configuration into a chromoMap2 project.

OUTPUT

My chromoMap2 plot

Click anywhere above to edit the title/text. Drag plot legends and custom text to reposition them.

Your chromoMap2 interactive visualization will appear here

Select one of the methods under Select Data tab to get started.

chromoMap2

A platform for comparative multi-omics visualization across multi-scale genomic landscapes.

Your chromoMap2 interactive visualization will appear here

DATA & PRIVACY POLICY

Creating chromoMap