HeatmapGenerator: high performance RNAseq and microarray visualization software suite to examine differential gene expression levels using an R and C++ hybrid computational pipeline.

Q2 Decision Sciences Source Code for Biology and Medicine Pub Date : 2014-12-24 eCollection Date: 2014-01-01 DOI:10.1186/s13029-014-0030-2
Bohdan B Khomtchouk, Derek J Van Booven, Claes Wahlestedt
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引用次数: 58

Abstract

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/. The Mac OS X direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_MAC_OSX.tar.gz/download. The Windows OS direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_WINDOWS.zip/download.

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HeatmapGenerator:高性能RNAseq和微阵列可视化软件套件,用于使用R和c++混合计算管道检查差异基因表达水平。
背景:使用热图的基因表达数据的图形可视化已经成为现代医学研究的一个组成部分。热图被广泛用于绘制基因表达水平的定量差异,例如用RNAseq和微阵列实验测量的差异,以提供转录组学景观的定性大规模视图。创建高质量的热图是一项计算密集型任务,通常需要相当多的编程经验,特别是针对手头的特定数据集定制特性时。方法:采用R编程语言、c++编程语言和OpenGL应用编程接口(API)开发出版级热图制作软件,制作工业级高性能图形。结果:我们为Windows OS和Mac OS X创建了一个名为HeatmapGenerator的图形用户界面(GUI)软件包,作为一个直观、用户友好的替代方案,使研究人员能够使用R图形创建出版物质量的热图,而不会牺牲他们想要的定制水平。HeatmapGenerator的简单之处在于,它只需要用户上传一个预格式化的输入文件,并下载公开可用的R软件语言,以及其他一些特定于操作系统的需求。高级特性,如颜色、文本标签、缩放、图例构建,甚至数据库存储,都可以在没有事先编程知识的情况下轻松定制。结论:我们提供了一个直观且用户友好的软件包,HeatmapGenerator,用于使用r的高分辨率彩色图形功能创建高质量,可定制的热图。该软件适用于Microsoft Windows和Apple Mac OS X. HeatmapGenerator在GNU通用公共许可证下发布,并在http://sourceforge.net/projects/heatmapgenerator/上公开发布。Mac OSX直接下载地址:http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_MAC_OSX.tar.gz/download。Windows操作系统的直接下载地址:http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_WINDOWS.zip/download。
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来源期刊
Source Code for Biology and Medicine
Source Code for Biology and Medicine Decision Sciences-Information Systems and Management
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期刊介绍: Source Code for Biology and Medicine is a peer-reviewed open access, online journal that publishes articles on source code employed over a wide range of applications in biology and medicine. The journal"s aim is to publish source code for distribution and use in the public domain in order to advance biological and medical research. Through this dissemination, it may be possible to shorten the time required for solving certain computational problems for which there is limited source code availability or resources.
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