Institute of Biophysics, CNR Unit at Trento, Trento, Italy.
Centre for Integrative Biology, University of Trento, Trento, Italy.
PLoS Comput Biol. 2018 Aug 13;14(8):e1006169. doi: 10.1371/journal.pcbi.1006169. eCollection 2018 Aug.
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.
核糖体图谱分析是一种用于在全基因组水平上研究翻译的强大技术,它提供了有关 RNA 上核糖体位置的独特信息。核糖体的最佳定位需要正确识别每个核糖体保护片段中的核糖体 P 位,这是确定翻译核糖体三核苷酸周期性的关键步骤,并能正确得出核糖体所在位置的结论。为了在核苷酸分辨率下确定核糖体足迹中的 P 位,需要精确估计其相对于保护片段的偏移量。这里我们介绍了 riboWaltz,这是一个用于计算最佳 P 位偏移量、诊断分析和可视化核糖体图谱分析数据的 R 包。与现有工具相比,riboWaltz 在多个案例研究中显示出了改进的 P 位估计和核糖体定位准确性。riboWaltz 是用 R 语言实现的,可以在 https://github.com/LabTranslationalArchitectomics/RiboWaltz 上作为 R 包获取。