RNA-Seq analysis in MeV.

Bioinformatics

Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

Published: November 2011

AI Article Synopsis

  • RNA-Seq is a high-throughput sequencing method used to accurately measure RNA transcript counts, but analyzing the resulting large datasets can be challenging for biologists.
  • MultiExperiment Viewer (MeV) is a user-friendly Java application designed for advanced gene expression data analysis, which has now been enhanced to support RNA-Seq data.
  • The updated MeV includes specific features for RNA-Seq analysis, such as automatic conversion from raw counts to RPKM/FPKM values and tools for detecting differential expression and functional annotation enrichment.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3208390PMC
http://dx.doi.org/10.1093/bioinformatics/btr490DOI Listing

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