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ContextMap 2: fast and accurate context-based RNA-seq mapping
BACKGROUND: Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411664/ https://www.ncbi.nlm.nih.gov/pubmed/25928589 http://dx.doi.org/10.1186/s12859-015-0557-5 |
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author | Bonfert, Thomas Kirner, Evelyn Csaba, Gergely Zimmer, Ralf Friedel, Caroline C |
author_facet | Bonfert, Thomas Kirner, Evelyn Csaba, Gergely Zimmer, Ralf Friedel, Caroline C |
author_sort | Bonfert, Thomas |
collection | PubMed |
description | BACKGROUND: Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes. RESULTS: In this article, we present ContextMap 2, a new and improved version of ContextMap. Its key novel features are: (i) a plug-in structure that allows easily integrating novel short read alignment programs with improved accuracy and runtime; (ii) context-based identification of insertions and deletions (indels); (iii) mapping of reads spanning an arbitrary number of exons and indels. ContextMap 2 using Bowtie, Bowtie 2 or BWA was evaluated on both simulated and real-life data from the recently published RGASP study. CONCLUSIONS: We show that ContextMap 2 generally combines similar or higher recall compared to other state-of-the-art approaches with significantly higher precision in read placement and junction and indel prediction. Furthermore, runtime was significantly lower than for the best competing approaches. ContextMap 2 is freely available at http://www.bio.ifi.lmu.de/ContextMap. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0557-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4411664 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44116642015-04-29 ContextMap 2: fast and accurate context-based RNA-seq mapping Bonfert, Thomas Kirner, Evelyn Csaba, Gergely Zimmer, Ralf Friedel, Caroline C BMC Bioinformatics Software BACKGROUND: Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes. RESULTS: In this article, we present ContextMap 2, a new and improved version of ContextMap. Its key novel features are: (i) a plug-in structure that allows easily integrating novel short read alignment programs with improved accuracy and runtime; (ii) context-based identification of insertions and deletions (indels); (iii) mapping of reads spanning an arbitrary number of exons and indels. ContextMap 2 using Bowtie, Bowtie 2 or BWA was evaluated on both simulated and real-life data from the recently published RGASP study. CONCLUSIONS: We show that ContextMap 2 generally combines similar or higher recall compared to other state-of-the-art approaches with significantly higher precision in read placement and junction and indel prediction. Furthermore, runtime was significantly lower than for the best competing approaches. ContextMap 2 is freely available at http://www.bio.ifi.lmu.de/ContextMap. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0557-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-04-17 /pmc/articles/PMC4411664/ /pubmed/25928589 http://dx.doi.org/10.1186/s12859-015-0557-5 Text en © Bonfert et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Bonfert, Thomas Kirner, Evelyn Csaba, Gergely Zimmer, Ralf Friedel, Caroline C ContextMap 2: fast and accurate context-based RNA-seq mapping |
title | ContextMap 2: fast and accurate context-based RNA-seq mapping |
title_full | ContextMap 2: fast and accurate context-based RNA-seq mapping |
title_fullStr | ContextMap 2: fast and accurate context-based RNA-seq mapping |
title_full_unstemmed | ContextMap 2: fast and accurate context-based RNA-seq mapping |
title_short | ContextMap 2: fast and accurate context-based RNA-seq mapping |
title_sort | contextmap 2: fast and accurate context-based rna-seq mapping |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4411664/ https://www.ncbi.nlm.nih.gov/pubmed/25928589 http://dx.doi.org/10.1186/s12859-015-0557-5 |
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