MmPalateMiRNA, an R package compendium illustrating analysis of miRNA microarray data.

Q2 Decision Sciences
Guy N Brock, Partha Mukhopadhyay, Vasyl Pihur, Cynthia Webb, Robert M Greene, M Michele Pisano
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引用次数: 35

Abstract

Background: MicroRNAs (miRNAs) constitute the largest family of noncoding RNAs involved in gene silencing and represent critical regulators of cell and tissue differentiation. Microarray expression profiling of miRNAs is an effective means of acquiring genome-level information of miRNA activation and inhibition, as well as the potential regulatory role that these genes play within a biological system. As with mRNA expression profiling arrays, miRNA microarrays come in a variety of platforms from numerous manufacturers, and there are a multitude of techniques available for reducing and analyzing these data.

Results: In this paper, we present an analysis of a typical two-color miRNA microarray experiment using publicly available packages from R and Bioconductor, the open-source software project for the analysis of genomic data. Covered topics include visualization, normalization, quality checking, differential expression, cluster analysis, miRNA target identification, and gene set enrichment analysis. Many of these tools carry-over from the analysis of mRNA microarrays, but with some notable differences that require special attention. The paper is presented as a "compendium" which, along with the accompanying R package MmPalateMiRNA, contains all of the experimental data and source code to reproduce the analyses contained in the paper.

Conclusions: The compendium presented in this paper will provide investigators with an access point for applying the methods available in R and Bioconductor for analysis of their own miRNA array data.

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mmpalatmirna,一个R包纲要,说明miRNA微阵列数据的分析。
背景:MicroRNAs (miRNAs)是参与基因沉默的最大的非编码rna家族,是细胞和组织分化的关键调控因子。miRNA的微阵列表达谱分析是获取miRNA激活和抑制的基因组水平信息以及这些基因在生物系统中发挥的潜在调节作用的有效手段。与mRNA表达谱阵列一样,miRNA微阵列来自众多制造商的各种平台,并且有多种技术可用于减少和分析这些数据。结果:在本文中,我们使用R和Bioconductor(用于基因组数据分析的开源软件项目)公开提供的软件包对一个典型的双色miRNA微阵列实验进行了分析。涵盖的主题包括可视化、规范化、质量检查、差异表达、聚类分析、miRNA目标鉴定和基因集富集分析。许多这些工具从mRNA微阵列的分析中延续下来,但有一些值得注意的差异需要特别注意。这篇论文以“纲要”的形式呈现,连同附带的R包MmPalateMiRNA,包含了所有的实验数据和源代码,以重现论文中包含的分析。结论:本文中提出的纲要将为研究人员提供一个接入点,用于应用R和Bioconductor中可用的方法来分析他们自己的miRNA阵列数据。
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
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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