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RNAvigate: Efficient exploration of RNA chemical probing datasets.

Patrick S IrvingKevin M Weeks
Published in: bioRxiv : the preprint server for biology (2023)
Chemical probing technologies enable high-throughput examination of diverse structural features of RNA including local nucleotide flexibility, RNA secondary structure, protein- and ligand-binding, through-space interaction networks, and multi-state structural ensembles. These layers of RNA structural information are often most incisive for understanding RNA structure-function relationships when combined with each other and when evaluated under structure- and function-altering conditions. Analysis of these complex data has required, often time consuming and awkward, juggling of multiple intermediate data files and software to create visualizations that support RNA-centered hypotheses. Here, we present the RNA visualization and graphical analysis toolset RNAvigate, developed as an easy-to-use and flexible Python library. RNAvigate currently integrates seven chemical probing data formats, nine secondary and tertiary structure formats, and eleven plot types. These features enable efficient exploration of nuanced relationships between chemical probing data, RNA structures, and motif annotations across multiple experimental samples. Modularity supports integration of new data types and plotting features. Compatibility with Jupyter Notebooks facilitates reproducibility and organization of multistep analyses and makes RNAvigate an ideal, time-effective, and non-burdensome platform for sharing full analysis pipelines. RNAvigate streamlines implementation of chemical probing strategies and accelerates discovery and characterization of diverse RNA-centric functions in biology.
Keyphrases
  • high throughput
  • electronic health record
  • nucleic acid
  • molecular dynamics simulations
  • single molecule
  • big data
  • social media
  • rna seq
  • protein protein