RNA-Seq analysis in MeV.
RNA-Seq analysis in MeV.
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DOI：
10.1093/bioinformatics/btr490
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发表时间：
2011-11-15
期刊：
影响因子：
--
通讯作者：
Quackenbush J
中科院分区：
文献类型：
--
作者：
Howe EA;Sinha R;Schlauch D;Quackenbush J
总结：RNA-Seq是一种令人兴奋的方法，它利用高通量测序的力量以前所未有的准确度测量RNA转录本计数。然而，从这个过程中产生的数据是非常大的，生物学家友好的工具来分析它是非常缺乏的。MultiExperiment Viewer（MeV）是一个基于Java的桌面应用程序，允许通过直观的图形用户界面对基因表达数据进行高级分析。在这里，我们报告了MeV的显着增强，允许使用这些熟悉、强大的工具分析RNA测序数据。我们还报告了几个RNA-Seq特定功能的MeV，解决了这种数据类型和传统基因表达数据之间的分析要求的差异。这些工具包括从原始计数数据到处理后的RPKM或FPKM值的自动转换功能，以及基于已发表方法的差异表达检测和功能注释富集检测。可用性：MeV 4.7版是用Java编写的，可以根据开源Artistic License 2.0版的条款免费下载。该网站（http：//mev.tm4.org/）载有完整的用户手册以及适合新用户的简短快速入门指南。联系方式：johnq@jimmy.harvard.edu
Summary: RNA-Seq is an exciting methodology that leverages the power of high-throughput sequencing to measure RNA transcript counts at an unprecedented accuracy. However, the data generated from this process are extremely large and biologist-friendly tools with which to analyze it are sorely lacking. MultiExperiment Viewer (MeV) is a Java-based desktop application that allows advanced analysis of gene expression data through an intuitive graphical user interface. Here, we report a significant enhancement to MeV that allows analysis of RNA-Seq data with these familiar, powerful tools. We also report the addition to MeV of several RNA-Seq-specific functions, addressing the differences in analysis requirements between this data type and traditional gene expression data. These tools include automatic conversion functions from raw count data to processed RPKM or FPKM values and differential expression detection and functional annotation enrichment detection based on published methods. Availability: MeV version 4.7 is written in Java and is freely available for download under the terms of the open-source Artistic License version 2.0. The website (http://mev.tm4.org/) hosts a full user manual as well as a short quick-start guide suitable for new users. Contact: johnq@jimmy.harvard.edu
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