In this tutorial, we will learn how to create and customise a heatmap to visualise our differential gene expression analysis results. We will use the R package pheatmap() which gives us great flexibility to add annotations to the rows and columns, and we will cover many different ways of customising the plot.
And as always, you can find the code I am using in this tutorial at biostatsquid.com, where you can also find a step by step explanation of the code. For this tutorial you will need R, or Rstudio, and you will need to install the pheatmap package.
Hope you like it!

Code explained: [ Ссылка ]
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Other interesting resources for heatmaps:
Some additional slides and tips when creating a heatmap: [ Ссылка ]...
Don't want to code? You can easily create your publication-ready heatmaps with this RShiny App:
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