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RNA-Seq analysis in MeV
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3208390/ https://www.ncbi.nlm.nih.gov/pubmed/21976420 http://dx.doi.org/10.1093/bioinformatics/btr490 |
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author | Howe, Eleanor A. Sinha, Raktim Schlauch, Daniel Quackenbush, John |
author_facet | Howe, Eleanor A. Sinha, Raktim Schlauch, Daniel Quackenbush, John |
author_sort | Howe, Eleanor A. |
collection | PubMed |
description | 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 |
format | Online Article Text |
id | pubmed-3208390 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-32083902011-11-04 RNA-Seq analysis in MeV Howe, Eleanor A. Sinha, Raktim Schlauch, Daniel Quackenbush, John Bioinformatics Applications Note 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 Oxford University Press 2011-11-15 2011-10-05 /pmc/articles/PMC3208390/ /pubmed/21976420 http://dx.doi.org/10.1093/bioinformatics/btr490 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Howe, Eleanor A. Sinha, Raktim Schlauch, Daniel Quackenbush, John RNA-Seq analysis in MeV |
title | RNA-Seq analysis in MeV |
title_full | RNA-Seq analysis in MeV |
title_fullStr | RNA-Seq analysis in MeV |
title_full_unstemmed | RNA-Seq analysis in MeV |
title_short | RNA-Seq analysis in MeV |
title_sort | rna-seq analysis in mev |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3208390/ https://www.ncbi.nlm.nih.gov/pubmed/21976420 http://dx.doi.org/10.1093/bioinformatics/btr490 |
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