Category Genomics>Gene Expression Analysis/Profiling/Tools

Abstract HeatMapper is an advanced visualization tool that allows the accurate and rapid interpretation of the data obtained by large scale gene expression profiling.

It provides the combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics. HeatMapper is an easy-to-use program that draws heat maps and displays clinical data next to the heat map.

HeatMapper also has the ability to save the heat map and clinical data as a picture.

HeatMapper Implementation -- HeatMapper, written in JAVA, uses comma-separated or tab-delimited text-files as input.

It requires two (2) files: one file containing a matrix of sample-sample similarity, i.e. Pearson correlation, Spearman correlation or Euclidean distance, and another separate file with sample related data.

In both files, similar sample ID's are used. Correlation files can be generated using tools such as Omniviz, GeneMaths and R/BioConductor, and sample data files can be created via Microsoft Excel.

Example files are available from the HeatMapper website. Alternatively, the tool can be adapted to communicate with a database.

In the manufacturer's laboratory, HeatMapper is connected to a MySQL database which further optimizes the workflow.

This version is available upon request from the manufacturer.

HeatMapper Results -- HeatMapper displays a triangular heat map. Sample-sample (dis-) similarity, i.e. Pearson correlation, Spearman correlation or Euclidean distance, is mapped to a color scale ranging from blue to red.

Dark blue relates to the negative extreme value of the metric, i.e. -1 for Pearson correlation, where dark red refers to the positive extreme value, i.e. 1 for Pearson correlation.

Sample related data, can be added via the menu and is subsequently plotted alongside the heat map diagonal.

Different entries in one sample characteristic are mapped to different colors, or, in the case of numeric data, shown as bars of which the size is proportional to the value.

Several options are available to customize the resulting visualization, such as zoom functionality and options to change the colors used in histograms or bars to indicate phenotypic or genotypic differences.

Further customization options include the ability to change the sample order, allowing a user to visualize the results of a different clustering algorithm, or to sort the data according to any user-defined order.

This can be accomplished via the 'Change sample order' menu-option, after which the order of the sample IDs can be inserted by typing them or by using the copy-paste feature.

Subsets of the original data can be created and viewed in any sequence.

Note: High-resolution images of the produced figures can be exported using the Portable Network Graphics (PNG) format.

HeatMapper provides several advantages over more traditional means of presenting results obtained via gene expression profiling and clustering analysis.

HeatMapper's pair-wise display of samples clearly indicates similarity in expression profiles.

By the combined visualization of sample versus sample similarities and sample characteristics, subclasses of samples sharing a commonality, such as a mutation in a particular gene, and a high similarity in expression profile can be readily identified.

Cluster assignments, made manually by the user, can then be added via the 'Add special values' menu option and displayed as a sample characteristic.

HeatMapper allows the accurate inspection of combinations of dataset characteristics, i.e. correlations and clustering results and sample related characteristics, i.e. survival time and gene expression levels.

System Requirements

Contact manufacturer.


Manufacturer Web Site HeatMapper

Price Contact manufacturer.

G6G Abstract Number 20321

G6G Manufacturer Number 100931