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RNA-Seq Analysis in MeV.
Bioinformatics. 2011 Oct 5;
Authors: Howe EA, Sinha R, Schlauch D, Quackenbush J
Abstract
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 is 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 v4.7 is written in Java and is freely available for download under the terms of the open-source Artistic License v2.0. The website, http://mev.tm4.org/, hosts a full user manual as well as a short quick-start guide suitable for new users. CONTACT: [email protected].
PMID: 21976420 [PubMed - as supplied by publisher]
More...
RNA-Seq Analysis in MeV.
Bioinformatics. 2011 Oct 5;
Authors: Howe EA, Sinha R, Schlauch D, Quackenbush J
Abstract
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 is 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 v4.7 is written in Java and is freely available for download under the terms of the open-source Artistic License v2.0. The website, http://mev.tm4.org/, hosts a full user manual as well as a short quick-start guide suitable for new users. CONTACT: [email protected].
PMID: 21976420 [PubMed - as supplied by publisher]
More...