A challenge to all cancer genomic studies is to visually explore the generated complex data in a meaningful way to extract relevant knowledge. We have written a review on that topic which has been published last week in Genome Medicine.
We group the different visualization options in three main types: Matrix Heatmaps, Genomic Coordinates and Networks (see Figure below), each of which is best suited to answer specific questions. And as the scientific community is headed towards producing multidimensional genomic profiling data, we present in the manuscript a selection of tools that are able to visualize multidimensional cancer genomics data (including Circos, Gitools, the Integrative Genomics Viewer, Cytoscape, Savant Genome Browser, StratomeX and platforms like cBio Cancer Genomics Portal, IntOGen, the UCSC Cancer Genomics Browser, the Regulome Explorer and the Cancer Genome Workbench) and use one or more of the three visualization types. Furthermore we describe four case studies that illustrate their use.
Hetmap Matrices, Genome Choordinates and Networks are the three common types to visualize multidimensional cancer genomics data.
You can access the article and the supplementary material at Genome Medicine. In the supplementary material, we provide a step by step description on how to produce some of the figures presented in the article. You can also find the article in our group’s publication list.
Michael P Schroeder, Abel Gonzalez-Perez and Nuria Lopez-Bigas. Visualizing multidimensional cancer genomics data. Genome Medicine 2013, 5:9 (31 January 2013).