maGUI: A Graphical User Interface for Analysis and Annotation of DNA Microarray Data

Q3 Computer Science

Open Bioinformatics Journal Pub Date : 2019-06-30 DOI:10.2174/1875036201912010040

Dhammapal Bharne, P. Kant, V. Vindal

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引用次数: 2

Abstract

maGUI is a graphical user interface designed to analyze microarray data produced from experiments performed on various platforms such as Affymetrix, Agilent, Illumina, and Nimblegen and so on, automatically. It follows an integrated workflow for pre-processing and analysis of the microarray data. The user may proceed from loading of microarray data to normalization, quality check, filtering, differential gene expression, principal component analysis, clustering and classification. It also provides miscellaneous applications such as gene set test and enrichment analysis for identifying gene symbols using Bioconductor packages. Further, the user can build a co-expression network for differentially expressed genes. Tables and figures generated during the analysis can be viewed and exported to local disks. The graphical user interface is very friendly especially for the biologists to perform the most microarray data analyses and annotations without much need of learning R command line programming. maGUI is an R package which can be downloaded freely from Comprehensive R Archive Network resource. It can be installed in any R environment with version 3.0.2 or above.

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maGUI：一个用于DNA微阵列数据分析和注释的图形用户界面

maGUI是一个图形用户界面，用于自动分析在各种平台(如Affymetrix, Agilent, Illumina和Nimblegen等)上进行的实验产生的微阵列数据。它遵循一个集成的工作流预处理和分析微阵列数据。用户可以从芯片数据的加载到归一化、质量检查、过滤、差异基因表达、主成分分析、聚类和分类。它还提供各种应用程序，如基因集测试和富集分析，以识别基因符号使用Bioconductor包。此外，用户可以为差异表达的基因建立一个共表达网络。分析过程中生成的表格和图表可以查看并导出到本地硬盘。图形用户界面非常友好，特别适合生物学家执行大多数微阵列数据分析和注释，而不需要学习R命令行编程。maGUI是一个R软件包，可以从综合R档案网络资源免费下载。它可以安装在任何3.0.2或更高版本的R环境中。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Open Bioinformatics Journal Computer Science-Computer Science (miscellaneous)

CiteScore

2.40

自引率

0.00%

发文量

期刊介绍： The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.