利用R和Bioconductor实现高通量基因组数据可视化

R. Yadav, P. Srivastava
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引用次数: 3

摘要

DNA微阵列技术旨在同时测量特定细胞或组织中许多基因的mRNA水平。分子生物学中的微阵列产生了庞大的数据集,需要严格的计算分析来提取生物信息,从而得出一些结论。从微阵列芯片的打印到杂交和扫描过程,它导致数据质量的变化,由于实际信息要么丢失,要么被过度表示。计算分析在处理微阵列结果中嵌入的生物信息以及比较不同条件下不同样品的基因表达结果以进行生物解释方面起着重要作用。微阵列基因表达数据的质量控制和可视化是一项基本但具有挑战性的任务。最流行的微阵列分析平台之一是Bioconductor,这是一个基于R编程语言的开源和开放开发软件项目,用于分析和理解基因组数据。本文介绍了利用GEO数据库GSE53890的数据对Affymetrix基因芯片进行质量评估的具体步骤,并参考可视化图对生物导体的质量控制包进行了详细分析。本文可以为任何从事微阵列分析的研究人员提供科学的解释,用于affymetrix芯片的质量控制分析。
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Visualization of High Throughput Genomic Data Using R and Bioconductor
DNA microarrays, technology aims at the measurement of mRNA levels in particular cells or tissues for many genes simultaneously. Microarray in molecular biology results in huge datasets that need rigorous computational analysis to extract biological information that lead to some conclusion. From printing of microarray chip to hybridization and scanning process it results in variability in quality of data due to which actual information is either lost or it is over represented. Computational analysis plays an important part related to the processing of the biological information embedded in microarray results and for comparing gene expression result obtained from different samples in different condition for biological interpretation. A basic, yet challenging task is quality control and visualization of microarray gene expression data. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project for the analysis and comprehension of genomic data, based on the R programming language. This paper describes specific procedures for conducting quality assessment of Affymetrix Gene chip using data from GEO database GSE53890 and describes quality control packages of bioconductor with reference to visualization plots for detailed analysis. This paper can be helpful for any researcher working on microarray analysis for quality control analysis of affymetrix chip along with scientific interpretations.
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