BMC BioinformaticsBioinformaticsPeer-reviewed journal article
SEQing: web-based visualization of iCLIP and RNA-seq data in an interactive python framework
Martin LewinskiiD, Yannik Bramkamp, Tino KösteriD, Dorothee StaigeriD
Abstract
BackgroundRNA-binding proteins interact with their target RNAs at specific sites. These binding sites can be determined genome-wide through individual nucleotide resolution crosslinking immunoprecipitation (iCLIP). Subsequently, the binding sites have to be visualized. So far, no visualization tool exists that is easily accessible but also supports restricted access so that data can be shared among collaborators. ResultsHere we present SEQing, a customizable interactive dashboard to visualize crosslink sites on target genes of RNA-binding proteins that have been obtained by iCLIP. Moreover, SEQing supports RNA-seq data that can be displayed in a diffrerent window tab. This allows, e.g. crossreferencing the iCLIP data with genes differentially expressed in mutants of the RBP and thus obtain some insights into a potential functional relevance of the binding sites. Additionally, detailed information on the target genes can be incorporated in another tab. ConclusionSEQing is written in Python3 and runs on Linux. The web-based access makes iCLIP data easily accessible, even with mobile devices. SEQing is customizable in many ways and has also the option to be secured by a password. The source code is available at https://github.com/malewins/SEQing.
- assay: imaging
- research focus: database / resource
- research focus: software / tool
- approach: experimental assay
- Citations
- 10
- FWCI
- 0.49
- Field percentile
- top 45%
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