Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
Bioinformatics. 2011 Nov 15;27(22):3209-10. doi: 10.1093/bioinformatics/btr490. Epub 2011 Oct 5.
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.
RNA-Seq 是一种令人兴奋的方法，它利用高通量测序的强大功能，以前所未有的准确性测量 RNA 转录本的数量。然而，该过程生成的数据非常庞大，而缺乏能够对其进行分析的、便于生物学家使用的工具。MultiExperiment Viewer（MeV）是一个基于 Java 的桌面应用程序，它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，我们报告了对 MeV 的一个重大增强，该增强允许使用这些熟悉的强大工具分析 RNA-Seq 数据。我们还报告了向 MeV 添加了几个特定于 RNA-Seq 的功能，这些功能解决了这种数据类型与传统基因表达数据在分析要求上的差异。这些工具包括从原始计数数据到经过处理的 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。
