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Transcript mapping based on dRNA-seq data
BACKGROUND: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016656/ https://www.ncbi.nlm.nih.gov/pubmed/24780064 http://dx.doi.org/10.1186/1471-2105-15-122 |
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author | Bischler, Thorsten Kopf, Matthias Voß, Björn |
author_facet | Bischler, Thorsten Kopf, Matthias Voß, Björn |
author_sort | Bischler, Thorsten |
collection | PubMed |
description | BACKGROUND: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems. RESULTS: We present RNAseg, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori. CONCLUSIONS: With our algorithm it is possible to identify operons and 5’- and 3’-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics. |
format | Online Article Text |
id | pubmed-4016656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40166562014-05-23 Transcript mapping based on dRNA-seq data Bischler, Thorsten Kopf, Matthias Voß, Björn BMC Bioinformatics Software BACKGROUND: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems. RESULTS: We present RNAseg, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori. CONCLUSIONS: With our algorithm it is possible to identify operons and 5’- and 3’-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics. BioMed Central 2014-04-29 /pmc/articles/PMC4016656/ /pubmed/24780064 http://dx.doi.org/10.1186/1471-2105-15-122 Text en Copyright © 2014 Bischler et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), 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 Bischler, Thorsten Kopf, Matthias Voß, Björn Transcript mapping based on dRNA-seq data |
title | Transcript mapping based on dRNA-seq data |
title_full | Transcript mapping based on dRNA-seq data |
title_fullStr | Transcript mapping based on dRNA-seq data |
title_full_unstemmed | Transcript mapping based on dRNA-seq data |
title_short | Transcript mapping based on dRNA-seq data |
title_sort | transcript mapping based on drna-seq data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016656/ https://www.ncbi.nlm.nih.gov/pubmed/24780064 http://dx.doi.org/10.1186/1471-2105-15-122 |
work_keys_str_mv | AT bischlerthorsten transcriptmappingbasedondrnaseqdata AT kopfmatthias transcriptmappingbasedondrnaseqdata AT voßbjorn transcriptmappingbasedondrnaseqdata |