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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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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. |
format | Online Article Text |
id | pubmed-6853685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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