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EpiMINE, a computational program for mining epigenomic data

机译：EpiMINE，用于挖掘表观基因组数据的计算程序

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Background In epigenetic research, both the increasing ease of high-throughput sequencing and a greater interest in genome-wide studies have resulted in an exponential flooding of epigenetic-related data in public domain. This creates an opportunity for exploring data outside the limits of any specific query-centred study. Such data have to undergo standard primary analyses that are accessible with multiple well-stabilized programs. Further downstream analyses, such as genome-wide comparative, correlative and quantitative analyses, are critical in deciphering key biological features. However, these analyses are only accessible for computational researchers and completely lack platforms capable of handling, analysing and linking multiple interdisciplinary datasets with efficient analytical methods. Results Here, we present EpiMINE, a program for mining epigenomic data. It is a user-friendly, stand-alone computational program designed to support multiple datasets, for performing genome-wide correlative and quantitative analysis of ChIP-seq and RNA-seq data. Using data available from the ENCODE project, we illustrated several features of EpiMINE through different biological scenarios to show how easy some known observations can be verified. These results highlight how these approaches can be helpful in identifying novel biological features. Conclusions EpiMINE performs different kinds of genome-wide quantitative and correlative analyses, using ChIP-seq- and RNA-seq-related datasets. Its framework enables it to be used by both experimental and computational researchers. EpiMINE can be downloaded from https://sourceforge.net/projects/epimine/ .
机译：背景技术在表观遗传学研究中，高通量测序的日益简便和对全基因组研究的浓厚兴趣都导致表观遗传学相关数据在公共领域呈指数级泛滥。这为探索以任何特定查询为中心的研究范围之外的数据提供了机会。此类数据必须经过标准的初步分析，并且可以通过多个稳定程序来访问。进一步的下游分析，例如全基因组的比较，相关和定量分析，对破译关键生物学特征至关重要。但是，这些分析仅供计算研究人员使用，并且完全缺乏能够使用有效的分析方法处理，分析和链接多个跨学科数据集的平台。结果在这里，我们介绍EpiMINE，这是一个挖掘表观基因组数据的程序。它是一种用户友好的独立计算程序，旨在支持多个数据集，以执行ChIP-seq和RNA-seq数据的全基因组相关和定量分析。使用来自ENCODE项目的数据，我们通过不同的生物学场景说明了EpiMINE的几个功能，以显示可以轻松验证某些已知观测值。这些结果突显了这些方法如何有助于识别新颖的生物学特征。结论EpiMINE使用ChIP-seq-和RNA-seq-相关的数据集进行了不同种类的全基因组定量和相关分析。它的框架使实验和计算研究人员都可以使用它。 EpiMINE可以从https://sourceforge.net/projects/epimine/下载。

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