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Bioinformatics and Computational Biology Solutions Using R and BioconductorVisualizing Data

Bioinformatics and Computational Biology Solutions Using R and Bioconductor: Visualizing Data [Visualization is an essential part of exploring, analyzing, and reporting data. Visualizations are used in all chapters in this monograph and in most scientific papers. Here we review some of the recurring concepts in visualizing genomic and biological data. We discuss scatterplots to investigate the dependency between pairs of variables, heatmaps for the visualization of matrix-like data, the visualization of distance relationships between objects, and the visualization of data along genomic coordinates.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Bioinformatics and Computational Biology Solutions Using R and BioconductorVisualizing Data

Part of the Statistics for Biology and Health Book Series
Editors: Gentleman, Robert; Carey, Vincent J.; Huber, Wolfgang; Irizarry, Rafael A.; Dudoit, Sandrine
Huber, W.; Li, X.; Gentleman, R.
Bioinformatics and Computational Biology Solutions Using R and Bioconductor — Jan 1, 2005
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Publisher
Springer New York
Copyright
© Springer Science+Business Media, Inc. 2005
ISBN
978-0-387-25146-2
Pages
161 –179
DOI
10.1007/0-387-29362-0_10
Publisher site
See Chapter on Publisher Site

Abstract

[Visualization is an essential part of exploring, analyzing, and reporting data. Visualizations are used in all chapters in this monograph and in most scientific papers. Here we review some of the recurring concepts in visualizing genomic and biological data. We discuss scatterplots to investigate the dependency between pairs of variables, heatmaps for the visualization of matrix-like data, the visualization of distance relationships between objects, and the visualization of data along genomic coordinates.]

Published: Jan 1, 2005

Keywords: Acute Myeloid Leukemia; Visualize Data; Visualization Method; Sense Strand; Antisense Strand

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