期刊论文详细信息
Source Code for Biology and Medicine
HeatmapGenerator: high performance RNAseq and microarray visualization software suite to examine differential gene expression levels using an R and C++ hybrid computational pipeline
Claes Wahlestedt1  Derek J Van Booven2  Bohdan B Khomtchouk1 
[1] Center for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th ST, Miami 33136, FL, USA;John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, 1501 NW 10th Avenue, Miami 33136, FL, USA
关键词: Computational genomics;    Next-Generation Sequencing (NGS);    OpenGL API;    C++ programming language;    R programming language;    Heatmap;    Microarray;    RNAseq;   
Others  :  1139265
DOI  :  10.1186/s13029-014-0030-2
 received in 2014-04-19, accepted in 2014-12-04,  发布年份 2014
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【 摘 要 】

Background

The graphical visualization of gene expression data using heatmaps has become an integral component of modern-day medical research. Heatmaps are used extensively to plot quantitative differences in gene expression levels, such as those measured with RNAseq and microarray experiments, to provide qualitative large-scale views of the transcriptonomic landscape. Creating high-quality heatmaps is a computationally intensive task, often requiring considerable programming experience, particularly for customizing features to a specific dataset at hand.

Methods

Software to create publication-quality heatmaps is developed with the R programming language, C++ programming language, and OpenGL application programming interface (API) to create industry-grade high performance graphics.

Results

We create a graphical user interface (GUI) software package called HeatmapGenerator for Windows OS and Mac OS X as an intuitive, user-friendly alternative to researchers with minimal prior coding experience to allow them to create publication-quality heatmaps using R graphics without sacrificing their desired level of customization. The simplicity of HeatmapGenerator is that it only requires the user to upload a preformatted input file and download the publicly available R software language, among a few other operating system-specific requirements. Advanced features such as color, text labels, scaling, legend construction, and even database storage can be easily customized with no prior programming knowledge.

Conclusion

We provide an intuitive and user-friendly software package, HeatmapGenerator, to create high-quality, customizable heatmaps generated using the high-resolution color graphics capabilities of R. The software is available for Microsoft Windows and Apple Mac OS X. HeatmapGenerator is released under the GNU General Public License and publicly available at: http://sourceforge.net/projects/heatmapgenerator/ webcite. The Mac OS X direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_MAC_OSX.tar.gz/download webcite. The Windows OS direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_WINDOWS.zip/download webcite.

【 授权许可】

   
2014 Khomtchouk et al.; licensee BioMed Central.

【 预 览 】
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Figure 4. 78KB Image download
Figure 3. 62KB Image download
Figure 2. 38KB Image download
Figure 1. 19KB Image download
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【 参考文献 】
  • [1]Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, Nordgren H, Farmer P, Praz V, Haibe-Kains B, Desmedt C, Larsimont D, Cardoso F, Peterse H, Nuyten D, Buyse M, Van de Vijver MJ, Bergh J, Piccart M, Delorenzi M: Gene expression profiling in breast cancer: understanding the molecular basis of histological grade to improve prognosis. J Natl Cancer Inst 2006, 98:262-272.
  • [2]Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J: TM4: a free, open-source system for microarray data management and analysis. Biotechniques 2003, 34(2):374-378.
  • [3]Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP: GenePattern 2.0. Nat Genet 2006, 38(5):500-501.
  • [4]Qlucore Omics Explorer. [http://www.qlucore.com]
  • [5]Gould J: GENE-E software hosted at the Broad Institute. [http://www.broadinstitute.org/cancer/software/GENE-E/]
  • [6]Turn your spreadsheet into a map. [http://www.openheatmap.com/]
  • [7]Wied P: Visualizing character distribution of texts on a keyboard while you’re typing. [http://www.patrick-wied.at/projects/heatmap-keyboard/]
  • [8]FLTK Fast Light Toolkit. [http://www.fltk.org/index.php]
  • [9]Wright RS, Haemal N, Sellers G, Lipchak B: OpenGL SuperBible: Comprehensive Tutorial Reference, 5th edition, Crawfordsville, IN: Addison-Wesley; 2010. 848.
  • [10]Prata S: C++ Primer Plus. 6th edition, Crawfordsville, IN: Addison-Wesley; 2012. 1200.
  • [11]R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2014.
  • [12]Liaw A, Gentleman R, Maechler M, Huber W, Warnes G: heatmap.2{gplots} R documentation: Enhanced Heat Map. [http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/gplots/html/heatmap.2.html]
  • [13]Warnes GR, Bolker B, Bonebakker L, Gentleman R, Huber W, Liaw A, Lumley T, Maechler M, Magnusson A, Moeller S, Schwartz M, Venables B: gplots: Various R programming tools for plotting data2013. R package version 2.12.1. [http://CRAN.R-project.org/package=gplots]
  • [14]Anders S, Pyl PT, Huber W: HTSeq - A Python framework to work with high-throughput sequencing data. Bioinformatics 2014, btu638:1-4.
  • [15]Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L: Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 2010, 289(5):511-515.
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