Microarray Gene Expression Data Generation and Pre-Processing of Moringa Oleifera Leaves for the Improvement of Medicinal Use

U. Shittu
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Abstract

Moringa oleifera is a plant species belonging to the family name called Moringaceae widely cultivated for human use. This study aimed to generate microarray gene expression data from the leaves of the Moringa oleifera plant and explore the usage of some tools available in the Bioconductor R package for the quality control. Six (6) young Moringa Oleifera leaves (YMOL) samples and six (6) old Moringa oleifera leaves (OMOL) samples were collected from the plant and processed for microarray data generation. Microarray gene expression raw data from the   leaves of the Moringa oleifera plants were generated, each in a CEL file format and the usage of some tools available in R programming Bioconductor open source and development software project were explored for the quality control of the data. Affycoretools were installed in the R environment for pre-processing of microarray raw data. AffyQCReport tools were used to generate a comprehensive quality control (QC) report for the microarray unnormalized raw data in PDF format. It is recommended that Gene chip robust multiarray analysis (GCRMA) method can be used for visual inspection, background correction, normalization and summarization of this microarray raw data.  The normalized microarray raw data can be used through the genetic engineering to improve the Moringa oleifera plant medicinal values in order to solve some medical problems especially with patients suffering from diabetes and hypertension and also can be of enormous importance in the fields of pharmacy and medicine at large.
辣木叶片微阵列基因表达数据生成及预处理提高药用价值
辣木(Moringa oleifera)是一种广泛种植供人类使用的辣木科植物。本研究旨在从辣木(Moringa oleifera)植物叶片中生成微阵列基因表达数据,并探索使用Bioconductor R软件包中的一些工具进行质量控制。采集6片辣木幼叶(YMOL)和6片辣木老叶(OMOL),进行微阵列数据处理。生成了辣木叶片的微阵列基因表达原始数据,每个数据都以CEL文件格式生成,并利用R编程中的一些工具和Bioconductor开源开发软件项目对数据进行质量控制。Affycoretools安装在R环境中,用于预处理微阵列原始数据。使用affyqreport工具生成PDF格式的微阵列非标准化原始数据的全面质量控制(QC)报告。建议采用基因芯片鲁棒多阵列分析(GCRMA)方法对该微阵列原始数据进行目视检查、背景校正、归一化和汇总。归一化微阵列原始数据可以通过基因工程来提高辣木植物的药用价值,以解决一些医疗问题,特别是糖尿病和高血压患者的医疗问题,在药学和医学领域具有重要意义。
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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