How to perform a hierarchical clustering using interactive heatmaps in Gitools

In the latest version of Gitools, version 2.1, we have improved the clustering of heatmaps. Here we explain in detail on how to perform and interpret the hierarchical clustering result – and why it is a bit different than the rest.

Hierarchical clustering in Gitools: The lines in the header represent the hierarchical tree splitting, the root at the bottom, the leafs at the top

Hierarchical clustering in Gitools: The lines in the heatmap header represent the hierarchical tree (Dendrogram) splitting at different levels. The root of the tree is located at the bottom, the leafs at the top. See video at YouTube

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Interactive heat-maps to explore biological data

Heat-maps are graphical representations of data where values in a matrix are represented following a color scale. This way of representing data has proven to be a very intuitive and useful to visualize biological data. With large and complex data being generated in biology and specially in Cancer Genomics, static heat-maps are a limited option for data exploration. Instead we need to be able to analyze data in an interactive way in order to be able to extract knowledge from it.

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List of tools to visualize multidimensional cancer genomics data

A while ago we published a review about multidimensional cancer genomics data visualization in Genome Medicine. There, we focused on effective and common visualization techniques for exploring oncogenomics data and we discussed a selection of tools that allow researchers to effectively visualize multidimensional oncogenomics datasets. Since our research field is constantly evolving we thought we could share an update of the tools and links.

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