Circos > Documentation > Tutorials > Recipes > Automating Heatmaps

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# 9 — Recipes

## 16. Automating Heatmaps

Before reading this tutorial, make sure that you understand how dynamic configuration parameters work (see Configuration Files Tutorial) and have read through the Automating Tracks Tutorial.

For this tutorial, I have created an image with 100 heat map tracks. The data for these tracks are gene densities computed across differently sized windows (0.5-50 Mb). The higest resolution file is data/8/17/genes.0.txt which samples density every 500kb. The lowest resolution file is data/8/17/genes.99.txt which samples density every 50,000kb (1/100th resolution of genes.0.txt).

The gene densities were designed so that each heat map interval occupies the same number of pixels along the map's circumference.

### changing heat map color

The color of the heat map is specified using a list of colors

color = red,green,blue

or a color list

color = spectral-11-div

For more about color lists, see the Configuration Files Tutorial.

The track counter can be used to dynamically change the color scheme. For example, as the track counter increases from 0 to 99, the definition

color = eval(sprintf("spectral-%d-div",remap_round(counter(plot),0,99,11,3)))

will assign a list to a track based on the counter. The assignment will range from spectral-11-div for the outer-most track, progressing through spectral-10-div, ..., and end at spectral-3-div for the inner-most track.

You can combine multiple color maps. Here, an orange sequential color list is added to a reversed blue sequential one.

color = eval(sprintf("blues-%d-seq-rev,oranges-%d-seq-rev",
remap_round(counter(plot),0,99,9,3),
remap_round(counter(plot),0,99,9,3)))

Given the reduced resolution of the inner-most track, reducing the number of colors in its heat map can make the figure more legible.