Department of Bioinformatics and Computational Biology

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Next Generation Clustered Heat Maps for TCGA Glioblastoma Multiforme

This page contains links to Next Generation Clustered Heat Maps (NG-CHM) for Glioblastoma Multiforme (GBM) data from the TCGA. NG-CHM are highly interactive, dynamic clustered heatmaps that enable the user to see an overview of the entire heatmap, and via interactive navigation controls, to zoom and pan across the heatmap to see details of the heatmap at many levels of resolution. Other interactive controls enable searching for specific heatmap entries, generating production quality PDFs, and linking out to information related to rows, columns, and individual heatmap entries. The user interface is mostly intuitive, although a few less commonly used features can only be accessed with the use of specific keys. These are documented in the Viewer user manual. Before using TCGA data, please read TCGA guidelines for publication and moratoriums .

We currently provide heatmaps in a size that can be viewed on laptop. We will shortly provide larger figures for users with higher resolution interfaces.

Gene by Sample Heatmap

This CHM displays expression levels for the 2000 most highly variable genes in the GBM dataset. The primary data layer shows the original (log transformed) mRNA expression levels. The second data layer (click Switch Data) shows the same data after row normalization.

Samples By Genes, small

Gene by Gene Heatmap

This CHM displays the correlations between the expression levels for the 1000 most highly variable genes in the GBM dataset. The primary data layer shows the Pearson correlation. The second data layer (click Switch Data) shows the Spearman correlation.

Genes By Genes, small

Sample by Sample Heatmap

This CHM displays the correlations between samples, based on the expression levels for the 1000 most highly variable genes in the GBM dataset. The primary data layer shows the Pearson correlation. The second data layer (click Switch Data) shows the Spearman correlation. The initial colormap for the second data layer only shows those samples with very high correlations between the most variable genes. Off-diagonal entries that are visible are likely to be duplicates, intentional (participant id the same) or unintentional.

Samples By Samples, small

Future Plans

We plan to provide further auxiliary information and other related heatmaps in the near future. Please contact John Weinstein or Bradley Broom if there is a specific feature or heatmap you would like to see.

Acknowledgements

The NG-CHM tool was developed by the MDACC Genome Data Analysis Center (GDAC) led by John Weinstein. Major contributors to the tool’s design and development include David Kane, Bradley Broom, Deepti Dodda, Lam Nguyen, Sid Acharya, Panna Shetty, Rehan Akbani, Chris Wakefield, and Allen Chang.