Nucleic Acids ResearchBioinformaticsPeer-reviewed journal article
miRSwitch: Detecting microRNA arm shift and switch events
Fabian KerniD, Jérémy AmandiD, Ilya S. SenatoroviD, Alina IsakovaiD, Christina BackesiD, Eckart U. MeeseiD, Andreas KelleriD, Tobias FehlmanniD
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 Alzheimers disease biomarker data set and from a comparison of tissues in Homo sapiens and Mus musculus. In summary, miRSwitch offers a broad range of customised arm switch analyses along with comprehensive visualisations, and is freely available at: https://www.ccb.uni-saarland.de/mirswitch/.
- organism: human
- organism: mouse
- assay: spatial transcriptomics
- research focus: cell type annotation
- approach: statistical model
- Citations
- 31
- FWCI
- 1.62
- Field percentile
- top 17%
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