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MethLAB: A graphical user interface package for the analysis of array-based DNA methylation data

机译:MethLAB:图形用户界面程序包,用于分析基于阵列的DNA甲基化数据

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Recent evidence suggests that DNA methylation changes may underlie numerous complex traits and diseases. The advent of commercial, array-based methods to interrogate DNA methylation has led to a profusion of epigenetic studies in the literature. Array-based methods, such as the popular Illumina GoldenGate and Infinium platforms, estimate the proportion of DNA methylated at single-base resolution for thousands of CpG sites across the genome. These arrays generate enormous amounts of data, but few software resources exist for efficient and flexible analysis of these data. We developed a software package called MethLAB (http://genetics.emory.edu/conneely/MethLAB) using R, an open source statistical language that can be edited to suit the needs of the user. MethLAB features a graphical user interface (GUI) with a menu-driven format designed to efficiently read in and manipulate array-based methylation data in a user-friendly manner. MethLAB tests for association between methylation and relevant phenotypes by fitting a separate linear model for each CpG site. These models can incorporate both continuous and categorical phenotypes and covariates, as well as fixed or random batch or chip effects. MethLAB accounts for multiple testing by controlling the false discovery rate (FDR) at a user-specified level. Standard output includes a spreadsheet-ready text file and an array of publication-quality figures. Considering the growing interest in and availability of DNA methylation data, there is a great need for user-friendly open source analytical tools. With MethLAB, we present a timely resource that will allow users with no programming experience to implement flexible and powerful analyses of DNA methylation data.
机译:最近的证据表明,DNA甲基化的变化可能是许多复杂性状和疾病的基础。询问DNA甲基化的基于阵列的商业化方法的出现导致文献中大量的表观遗传学研究。基于阵列的方法(例如流行的Illumina GoldenGate和Infinium平台)估计了整个基因组中成千上万个CpG位点在单碱基分辨率下甲基化的DNA比例。这些阵列生成大量数据,但是很少有软件资源可以有效,灵活地分析这些数据。我们使用R开发了一种名为MethLAB(http://genetics.emory.edu/conneely/MethLAB)的软件包,R是一种开放源代码统计语言,可以对其进行编辑以满足用户的需求。 MethLAB具有菜单驱动格式的图形用户界面(GUI),该格式旨在以用户友好的方式有效地读取和操作基于阵列的甲基化数据。 MethLAB通过为每个CpG位点拟合一个单独的线性模型来测试甲基化和相关表型之间的关联。这些模型可以包含连续和分类表型和协变量,以及固定或随机的批或芯片效应。 MethLAB通过在用户指定的级别上控制错误发现率(FDR)来进行多次测试。标准输出包括可用于电子表格的文本文件和一系列具有出版质量的图形。考虑到人们对DNA甲基化数据的兴趣与日俱增,非常需要用户友好的开源分析工具。借助MethLAB,我们可以提供及时的资源,使没有编程经验的用户可以对DNA甲基化数据进行灵活而强大的分析。

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