Please use this identifier to cite or link to this item:
doi:10.22028/D291-36012
Title: | miRSwitch: detecting microRNA arm shift and switch events |
Author(s): | Kern, Fabian Amand, Jeremy Senatorov, Ilya Isakova, Alina Backes, Christina Meese, Eckart Keller, Andreas Fehlmann, Tobias |
Language: | English |
Title: | Nucleic Acids Research |
Volume: | 48 |
Issue: | W1 |
Pages: | W268–W274 |
Publisher/Platform: | Oxford University Press |
Year of Publication: | 2020 |
DDC notations: | 610 Medicine and health |
Publikation type: | Journal Article |
Abstract: | Arm selection, the preferential expression of a 3′ or 5′ mature microRNA (miRNA), is a highly dynamic and tissue-specific process. Time-dependent expression shifts or switches between the arms are also relevant for human diseases. We present miRSwitch, a web server to facilitate the analysis and interpretation of arm selection events. Our species-independent tool evaluates pre-processed small non-coding RNA sequencing (sncRNA-seq) data, i.e. expression matrices or output files from miRNA quantification tools (miRDeep2, miRMaster, sRNAbench). miRSwitch highlights potential changes in the distribution of mature miRNAs from the same precursor. Group comparisons from one or several user-provided annotations (e.g. disease states) are possible. Results can be dynamically adjusted by choosing from a continuous range of highly specific to very sensitive parameters. Users can compare potential arm shifts in the provided data to a human reference map of pre-computed arm shift frequencies. We created this map from 46 tissues and 30 521 samples. As case studies we present novel arm shift information in a Alzheimer’s disease biomarker data set and from a comparison of tissues in Homo sapiens and Mus musculus. In summary, miRSwitch offers a broad range of customized arm switch analyses along with comprehensive visualizations, and is freely available at: https://www.ccb.uni-saarland.de/mirswitch/. |
DOI of the first publication: | 10.1093/nar/gkaa323 |
Link to this record: | urn:nbn:de:bsz:291--ds-360129 hdl:20.500.11880/32808 http://dx.doi.org/10.22028/D291-36012 |
ISSN: | 1362-4962 0305-1048 |
Date of registration: | 19-Apr-2022 |
Faculty: | M - Medizinische Fakultät |
Department: | M - Humangenetik M - Medizinische Biometrie, Epidemiologie und medizinische Informatik |
Professorship: | M - Univ.-Prof. Dr. Andreas Keller M - Prof. Dr. Eckhart Meese |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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gkaa323.pdf | 1,34 MB | Adobe PDF | View/Open |
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