Cargando…

Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses

As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of RNA-Seq data often starts with the mapping of millions of short reads back to the genome or transcriptome, a proc...

Descripción completa

Detalles Bibliográficos
Autores principales: Storvall, Helena, Ramsköld, Daniel, Sandberg, Rickard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3548888/
https://www.ncbi.nlm.nih.gov/pubmed/23349747
http://dx.doi.org/10.1371/journal.pone.0053822
_version_ 1782256385197604864
author Storvall, Helena
Ramsköld, Daniel
Sandberg, Rickard
author_facet Storvall, Helena
Ramsköld, Daniel
Sandberg, Rickard
author_sort Storvall, Helena
collection PubMed
description As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of RNA-Seq data often starts with the mapping of millions of short reads back to the genome or transcriptome, a process in which some reads are found to map equally well to multiple genomic locations (multimapping reads). We have developed the Minimum Unique Length Tool (MULTo), a framework for efficient and comprehensive representation of mappability information, through identification of the shortest possible length required for each genomic coordinate to become unique in the genome and transcriptome. Using the minimum unique length information, we have compared different uniqueness compensation approaches for transcript expression level quantification and demonstrate that the best compensation is achieved by discarding multimapping reads and correctly adjusting gene model lengths. We have also explored uniqueness within specific regions of the mouse genome and enhancer mapping experiments. Finally, by making MULTo available to the community we hope to facilitate the use of uniqueness compensation in RNA-Seq analysis and to eliminate the need to make additional mappability files.
format Online
Article
Text
id pubmed-3548888
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-35488882013-01-24 Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses Storvall, Helena Ramsköld, Daniel Sandberg, Rickard PLoS One Research Article As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of RNA-Seq data often starts with the mapping of millions of short reads back to the genome or transcriptome, a process in which some reads are found to map equally well to multiple genomic locations (multimapping reads). We have developed the Minimum Unique Length Tool (MULTo), a framework for efficient and comprehensive representation of mappability information, through identification of the shortest possible length required for each genomic coordinate to become unique in the genome and transcriptome. Using the minimum unique length information, we have compared different uniqueness compensation approaches for transcript expression level quantification and demonstrate that the best compensation is achieved by discarding multimapping reads and correctly adjusting gene model lengths. We have also explored uniqueness within specific regions of the mouse genome and enhancer mapping experiments. Finally, by making MULTo available to the community we hope to facilitate the use of uniqueness compensation in RNA-Seq analysis and to eliminate the need to make additional mappability files. Public Library of Science 2013-01-18 /pmc/articles/PMC3548888/ /pubmed/23349747 http://dx.doi.org/10.1371/journal.pone.0053822 Text en © 2013 Storvall et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Storvall, Helena
Ramsköld, Daniel
Sandberg, Rickard
Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses
title Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses
title_full Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses
title_fullStr Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses
title_full_unstemmed Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses
title_short Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses
title_sort efficient and comprehensive representation of uniqueness for next-generation sequencing by minimum unique length analyses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3548888/
https://www.ncbi.nlm.nih.gov/pubmed/23349747
http://dx.doi.org/10.1371/journal.pone.0053822
work_keys_str_mv AT storvallhelena efficientandcomprehensiverepresentationofuniquenessfornextgenerationsequencingbyminimumuniquelengthanalyses
AT ramskolddaniel efficientandcomprehensiverepresentationofuniquenessfornextgenerationsequencingbyminimumuniquelengthanalyses
AT sandbergrickard efficientandcomprehensiverepresentationofuniquenessfornextgenerationsequencingbyminimumuniquelengthanalyses