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救命--表达数据的综合分析。

Mayday--integrative analytics for expression data.

机构信息

Center for Bioinformatics Tübingen, University of Tübingen, Sand 14, 72076 Tübingen, Germany.

出版信息

BMC Bioinformatics. 2010 Mar 9;11:121. doi: 10.1186/1471-2105-11-121.

DOI:10.1186/1471-2105-11-121
PMID:20214778
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2848234/
Abstract

BACKGROUND

DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files.

RESULTS

We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved.

CONCLUSIONS

We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org.

摘要

背景

DNA 微阵列已成为大规模基因表达和表观基因组学分析的标准方法。生成数据的日益复杂性和内在噪声使得可视化数据探索变得越来越重要。快速部署新方法以及将预定义的、易于应用的方法与程序员对数据的访问相结合,是任何分析框架的重要要求。Mayday 是一个开源平台,重点是可视化数据探索和分析。提供了许多用于剖析复杂数据集的聚类、机器学习和分类内置方法。可以轻松编写插件,以多种方式扩展 Mayday 的功能。作为 Java 程序,Mayday 与平台无关,可以作为 Java WebStart 应用程序使用,无需任何安装。Mayday 可以从多种文件格式导入数据,包括数据库连接,用于高效的数据组织。提供了许多交互式可视化工具,包括箱线图、轮廓图、主成分图和热图,可以使用元数据增强,并以出版质量的向量文件导出。

结果

我们重写了 Mayday 的核心部分,使其更高效,并为未来的发展做好准备。在大量新插件中,包括自动化处理框架、动态过滤、新的和高效的聚类方法、机器学习模块和数据库连接。可以使用内置的 R 终端和集成的 SQL 查询界面进行广泛的手动数据分析。我们的可视化框架变得更加强大,添加了新的绘图类型并改进了现有的绘图。

结论

我们提出了 Mayday 的一个重大扩展,这是一个非常通用的开源框架,用于高效的微阵列数据分析,专为生物学家和生物信息学家设计。大多数日常任务都已经涵盖。大量可用的插件以及使用编译插件和特定脚本进行扩展的可能性,允许 Mayday 快速适应非常专业的数据探索。Mayday 可在 http://microarray-analysis.org 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/309679b79468/1471-2105-11-121-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/15bf6704d2cb/1471-2105-11-121-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/863e17e075f3/1471-2105-11-121-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/51a81fd0fa83/1471-2105-11-121-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/59270b0e778d/1471-2105-11-121-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/83b9c4db2a16/1471-2105-11-121-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/3dcc1a05aaae/1471-2105-11-121-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/309679b79468/1471-2105-11-121-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/15bf6704d2cb/1471-2105-11-121-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/863e17e075f3/1471-2105-11-121-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/51a81fd0fa83/1471-2105-11-121-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/59270b0e778d/1471-2105-11-121-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/83b9c4db2a16/1471-2105-11-121-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/3dcc1a05aaae/1471-2105-11-121-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1826/2848234/309679b79468/1471-2105-11-121-7.jpg

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