RNA-Seq analysis in MeV

被引：424

作者：

Howe, Eleanor A. ^{[1
,2
]}

Sinha, Raktim ^{[1
]}

Schlauch, Daniel ^{[1
]}

Quackenbush, John ^{[1
,3
,4
]}

机构：

[1] Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02115 USA

[2] Univ Oxford, Dept Stat, Oxford OX1 3TG, England

[3] Dana Farber Canc Inst, Dept Canc Biol, Boston, MA 02115 USA

[4] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA

来源：

BIOINFORMATICS | 2011年 / 27卷 / 22期

关键词：

DIFFERENTIAL EXPRESSION ANALYSIS; ALIGNMENT; PACKAGE; TM4;

D O I：

10.1093/bioinformatics/btr490

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页码：3209 / 3210

页数：2

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