HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics

<p>Abstract</p> <p>Background</p> <p>Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not...

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Main Authors: Moorhouse Michael J, Horsman Sebastiaan, Delwel Ruud, Bijl Maarten A, Sanders Mathijs A, Verhaak Roel GW, van der Spek Peter J, Löwenberg Bob, Valk Peter JM
Format: Article
Language:English
Published: BMC 2006-07-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/7/337
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spelling doaj-62162e7f5c524c3bb7efeaed3c7558e32020-11-24T23:31:47ZengBMCBMC Bioinformatics1471-21052006-07-017133710.1186/1471-2105-7-337HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristicsMoorhouse Michael JHorsman SebastiaanDelwel RuudBijl Maarten ASanders Mathijs AVerhaak Roel GWvan der Spek Peter JLöwenberg BobValk Peter JM<p>Abstract</p> <p>Background</p> <p>Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata.</p> <p>Results</p> <p>We have developed a tool called the HeatMapper that provides such visualizations in a dynamic and flexible manner and is available from <url>http://www.erasmusmc.nl/hematologie/heatmapper/</url>.</p> <p>Conclusion</p> <p>The HeatMapper allows an accessible and comprehensive visualization of the results of gene expression profiling and cluster analysis.</p> http://www.biomedcentral.com/1471-2105/7/337
collection DOAJ
language English
format Article
sources DOAJ
author Moorhouse Michael J
Horsman Sebastiaan
Delwel Ruud
Bijl Maarten A
Sanders Mathijs A
Verhaak Roel GW
van der Spek Peter J
Löwenberg Bob
Valk Peter JM
spellingShingle Moorhouse Michael J
Horsman Sebastiaan
Delwel Ruud
Bijl Maarten A
Sanders Mathijs A
Verhaak Roel GW
van der Spek Peter J
Löwenberg Bob
Valk Peter JM
HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
BMC Bioinformatics
author_facet Moorhouse Michael J
Horsman Sebastiaan
Delwel Ruud
Bijl Maarten A
Sanders Mathijs A
Verhaak Roel GW
van der Spek Peter J
Löwenberg Bob
Valk Peter JM
author_sort Moorhouse Michael J
title HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
title_short HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
title_full HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
title_fullStr HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
title_full_unstemmed HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
title_sort heatmapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2006-07-01
description <p>Abstract</p> <p>Background</p> <p>Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining sample-gene heatmaps and sample characteristics. This method is not optimal for comparing individual samples or groups of samples. Here, we describe an approach to visually integrate the results of unsupervised and supervised cluster analysis using a correlation plot and additional sample metadata.</p> <p>Results</p> <p>We have developed a tool called the HeatMapper that provides such visualizations in a dynamic and flexible manner and is available from <url>http://www.erasmusmc.nl/hematologie/heatmapper/</url>.</p> <p>Conclusion</p> <p>The HeatMapper allows an accessible and comprehensive visualization of the results of gene expression profiling and cluster analysis.</p>
url http://www.biomedcentral.com/1471-2105/7/337
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