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Jeske, T. ; Huypens, P. ; Stirm, L. ; Höckele, S. ; Wurmser, C.M.* ; Böhm, A. ; Weigert, C. ; Staiger, H. ; Klein, C.* ; Beckers, J. ; Hastreiter, M.

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

Bioinformatics 35, 4834-4836 (2019)
Publ. Version/Full Text Postprint Research data DOI PMC
Open Access Green
A 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.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Cd-hit
ISSN (print) / ISBN 1367-4803
Journal Bioinformatics
Quellenangaben Volume: 35, Issue: 22, Pages: 4834-4836 Article Number: , Supplement: ,
Publisher Oxford University Press
Publishing Place Oxford
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Experimental Genetics (IEG)
Institute of Diabetes Research and Metabolic Diseases (IDM)