Please use this identifier to cite or link to this item:
doi:10.22028/D291-38143
Title: | isomiRdb : microRNA expression at isoform resolution |
Author(s): | Aparicio-Puerta, Ernesto Hirsch, Pascal Schmartz, Georges P. Fehlmann, Tobias Keller, Verena Engel, Annika Kern, Fabian Hackenberg, Michael Keller, Andreas |
Language: | English |
Title: | Nucleic Acids Research |
Publisher/Platform: | Oxford University Press |
Year of Publication: | 2022 |
DDC notations: | 610 Medicine and health |
Publikation type: | Journal Article |
Abstract: | A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients’ samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (>1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb. |
DOI of the first publication: | 10.1093/nar/gkac884 |
URL of the first publication: | https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkac884/6761735 |
Link to this record: | urn:nbn:de:bsz:291--ds-381432 hdl:20.500.11880/34448 http://dx.doi.org/10.22028/D291-38143 |
ISSN: | 1362-4962 0305-1048 |
Date of registration: | 22-Nov-2022 |
Faculty: | M - Medizinische Fakultät |
Department: | M - Medizinische Biometrie, Epidemiologie und medizinische Informatik |
Professorship: | M - Univ.-Prof. Dr. Andreas Keller |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
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gkac884.pdf | 1,86 MB | Adobe PDF | View/Open |
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