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riboWaltz: Optimization of ribosome P-site positioning in ribosome profiling data.

Fabio LauriaToma TebaldiPaola BernabòEwout Joan Nicolaas GroenThomas Henry GillingwaterGabriella Viero
Published in: PLoS computational biology (2018)
Ribosome profiling is a powerful technique used to study translation at the genome-wide level, generating unique information concerning ribosome positions along RNAs. Optimal localization of ribosomes requires the proper identification of the ribosome P-site in each ribosome protected fragment, a crucial step to determine the trinucleotide periodicity of translating ribosomes, and draw correct conclusions concerning where ribosomes are located. To determine the P-site within ribosome footprints at nucleotide resolution, the precise estimation of its offset with respect to the protected fragment is necessary. Here we present riboWaltz, an R package for calculation of optimal P-site offsets, diagnostic analysis and visual inspection of ribosome profiling data. Compared to existing tools, riboWaltz shows improved accuracies for P-site estimation and neat ribosome positioning in multiple case studies. riboWaltz was implemented in R and is available as an R package at https://github.com/LabTranslationalArchitectomics/RiboWaltz.
Keyphrases
  • genome wide
  • single cell
  • dna methylation
  • electronic health record
  • big data
  • machine learning
  • quality control
  • single molecule
  • copy number