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DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences

SUMMARY: Despite their fundamental role in various biological processes, the analysis of small RNA sequencing data remains a challenging task. Major obstacles arise when short RNA sequences map to multiple locations in the genome, align to regions that are not annotated or underwent post-transcripti...

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Autores principales: Jeske, Tim, Huypens, Peter, Stirm, Laura, Höckele, Selina, Wurmser, Christine M, Böhm, Anja, Weigert, Cora, Staiger, Harald, Klein, Christoph, Beckers, Johannes, Hastreiter, Maximilian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6853685/
https://www.ncbi.nlm.nih.gov/pubmed/31228198
http://dx.doi.org/10.1093/bioinformatics/btz495
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author Jeske, Tim
Huypens, Peter
Stirm, Laura
Höckele, Selina
Wurmser, Christine M
Böhm, Anja
Weigert, Cora
Staiger, Harald
Klein, Christoph
Beckers, Johannes
Hastreiter, Maximilian
author_facet Jeske, Tim
Huypens, Peter
Stirm, Laura
Höckele, Selina
Wurmser, Christine M
Böhm, Anja
Weigert, Cora
Staiger, Harald
Klein, Christoph
Beckers, Johannes
Hastreiter, Maximilian
author_sort Jeske, Tim
collection PubMed
description SUMMARY: Despite their fundamental role in various biological processes, the analysis of small RNA sequencing data remains a challenging task. Major obstacles arise when short RNA sequences map to multiple locations in the genome, align to regions that are not annotated or underwent post-transcriptional changes which hamper accurate mapping. In order to tackle these issues, we present a novel profiling strategy that circumvents the need for read mapping to a reference genome by utilizing the actual read sequences to determine expression intensities. After differential expression analysis of individual sequence counts, significant sequences are annotated against user defined feature databases and clustered by sequence similarity. This strategy enables a more comprehensive and concise representation of small RNA populations without any data loss or data distortion. AVAILABILITY AND IMPLEMENTATION: Code and documentation of our R package at http://ibis.helmholtz-muenchen.de/deus/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-68536852019-11-19 DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences Jeske, Tim Huypens, Peter Stirm, Laura Höckele, Selina Wurmser, Christine M Böhm, Anja Weigert, Cora Staiger, Harald Klein, Christoph Beckers, Johannes Hastreiter, Maximilian Bioinformatics Applications Notes SUMMARY: Despite their fundamental role in various biological processes, the analysis of small RNA sequencing data remains a challenging task. Major obstacles arise when short RNA sequences map to multiple locations in the genome, align to regions that are not annotated or underwent post-transcriptional changes which hamper accurate mapping. In order to tackle these issues, we present a novel profiling strategy that circumvents the need for read mapping to a reference genome by utilizing the actual read sequences to determine expression intensities. After differential expression analysis of individual sequence counts, significant sequences are annotated against user defined feature databases and clustered by sequence similarity. This strategy enables a more comprehensive and concise representation of small RNA populations without any data loss or data distortion. AVAILABILITY AND IMPLEMENTATION: Code and documentation of our R package at http://ibis.helmholtz-muenchen.de/deus/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-11-15 2019-06-22 /pmc/articles/PMC6853685/ /pubmed/31228198 http://dx.doi.org/10.1093/bioinformatics/btz495 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Jeske, Tim
Huypens, Peter
Stirm, Laura
Höckele, Selina
Wurmser, Christine M
Böhm, Anja
Weigert, Cora
Staiger, Harald
Klein, Christoph
Beckers, Johannes
Hastreiter, Maximilian
DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences
title DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences
title_full DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences
title_fullStr DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences
title_full_unstemmed DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences
title_short DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences
title_sort deus: an r package for accurate small rna profiling based on differential expression of unique sequences
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6853685/
https://www.ncbi.nlm.nih.gov/pubmed/31228198
http://dx.doi.org/10.1093/bioinformatics/btz495
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