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.
Some time ago we proposed the use of interactive heat-maps to explore biological data (Perez-Llamas and Lopez-Bigas, PLoS ONE 2011) and we developed Gitools as an application devoted to this task. In an interactive heat-map every cell is associated to a set of values and annotations than can be visualized in colours and navigated interactively. A number of actions can be performed over the heat-map, which help to explore and interpret the data effectively, such as search, filter by value or label, cluster the heat-map, sort rows and columns by different criteria, move them freely, perform a number of analyses, etc.
Here I post a short video showing some basic features of interactive heat-maps in Gitools 2 to demonstrate how it works.
Both Gitools and jHeatmap are open source projects and you are invited to visit their web pages, and start using them.
jHeatmap web: http://jheatmap.github.io/jheatmap, source code: https://github.com/jheatmap/jheatmap
Gitools web: http://www.gitools.org, source code: https://github.com/gitools/gitools
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