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ChimericFragments: computation, analysis and visualization of global RNA networks.

Malte SiemersAnne LippegausKai Pappenfort
Published in: NAR genomics and bioinformatics (2024)
RNA-RNA interactions are a key feature of post-transcriptional gene regulation in all domains of life. While ever more experimental protocols are being developed to study RNA duplex formation on a genome-wide scale, computational methods for the analysis and interpretation of the underlying data are lagging behind. Here, we present ChimericFragments, an analysis framework for RNA-seq experiments that produce chimeric RNA molecules. ChimericFragments implements a novel statistical method based on the complementarity of the base-pairing RNAs around their ligation site and provides an interactive graph-based visualization for data exploration and interpretation. ChimericFragments detects true RNA-RNA interactions with high precision and is compatible with several widely used experimental procedures such as RIL-seq, LIGR-seq or CLASH. We further demonstrate that ChimericFragments enables the systematic detection of novel RNA regulators and RNA-target pairs with crucial roles in microbial physiology and virulence. ChimericFragments is written in Julia and available at: https://github.com/maltesie/ChimericFragments.
Keyphrases
  • rna seq
  • genome wide
  • single cell
  • nucleic acid
  • escherichia coli
  • dna methylation
  • staphylococcus aureus
  • stem cells
  • mesenchymal stem cells
  • big data
  • deep learning
  • microbial community