Abstract
Clustered heat maps are the most frequently used graphics for visualization and interpretation of genome-scale molecular profiling data in biology. Construction of a heat map generally requires the assistance of a biostatistician or bioinformatics analyst capable of working in R or a similar programming language to transform the study data, perform hierarchical clustering, and generate the heat map. Our web-based Interactive Heat Map Builder can be used by investigators with no bioinformatics experience to generate high-caliber, publication quality maps. Preparation of the data and construction of a heat map is rarely a simple linear process. Our tool allows a user to move back and forth iteratively through the various stages of map generation to try different options and approaches. Finally, the heat map the builder creates is available in several forms, including an interactive Next-Generation Clustered Heat Map that can be explored dynamically to investigate the results more fully.
Highlights
Clustered heat maps are the most frequently used graphics for visualization and interpretation of genome-scale molecular profiling data in biology
Any further responses from the reviewers can be found at the end of the article Introduction Many thousands of publications on genomics studies include clustered heat maps (CHMs) because the hierarchical clustering and intuitive visualization provide insight into the relationships among sample sub-groups and key biological processes[1,2,3,4,5,6,7,8]
We focus on gene expression data from The Cancer Genome Atlas (TCGA) bladder cancer project[12,13]
Summary
Any reports and responses or comments on the article can be found at the end of the article. Construction of a CHM requires data transformation, application of clustering methods, association of covariate (classification) data, and production of the heat map visualization Those tasks require the assistance of an analyst with biostatistics or bioinformatics skills who can work in R or a similar language to manipulate the study data and generate the map. Our Interactive CHM Builder is a web-based tool for data transformation, clustering, and generation of high-quality heat maps. It can be used by investigators with no bioinformatics experience and only modest exposure to biostatistical methods. Other methods of producing NG-CHMs, including an R library and a set of tools for the Galaxy platform[10,11], are described at https://www.ngchm.net/
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