PLoS Computational Biology · 2018 · 221 citations · 35 references
Structural BioinformaticsGeneticsMolecular BiologyOptimal LocalizationGenomicsSequence AlignmentRibosome ProfilingR PackageMolecular DiagnosticsProteomicsRna Structure PredictionSequence AnalysisRibosome Profiling DataProtein Structure PredictionProtein ModelingFunctional GenomicsBioinformaticsStructural BiologyNatural SciencesComputational BiologySystems BiologyMedicine
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.
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BEDTools: a flexible suite of utilities for comparing genomic features
Aaron R. Quinlan, Ira M. Hall · Bioinformatics · 2010 · 28.9K citations · Full text
Mammalian microRNAs predominantly act to decrease target mRNA levels
Huili Guo, Nicholas T. Ingolia, Jonathan S. Weissman et al. · Nature · 2010 · 3.9K citations · Full text
Nicholas T. Ingolia, Gloria A. Brar, Silvi Rouskin et al. · Nature Protocols · 2012 · 1.4K citations · Full text
Ribosome-protected Mrna Fragments, Functional Genomics, Engineering +12