Riboviz 2: a flexible and robust ribosome profiling data analysis and visualization workflow.

Alexander L Cope,John Favate,Michael Jackson,Siyin Xue,Felicity Anderson,Edward W J Wallace,Peter Tilton,Emma Mackenzie,Amanda Mok,Liana F Lareau,Sophie M Winterbourne,Vikram Shivakumar,Anna Kurowska,Junchen Liu,Kostas Kavoussanakis,Premal Shah,Alfonso Valencia

doi:10.1093/bioinformatics/btac093

Abstract

MotivationRibosome profiling, or Ribo-seq, is the state-of-the-art method for quantifying protein synthesis in living cells. Computational analysis of Ribo-seq data remains challenging due to the complexity of the procedure, as well as variations introduced for specific organisms or specialized analyses.ResultsWe present riboviz 2, an updated riboviz package, for the comprehensive transcript-centric analysis and visualization of Ribo-seq data. riboviz 2 includes an analysis workflow built on the Nextflow workflow management system for end-to-end processing of Ribo-seq data. riboviz 2 has been extensively tested on diverse species and library preparation strategies, including multiplexed samples. riboviz 2 is flexible and uses open, documented file formats, allowing users to integrate new analyses with the pipeline.Availability and implementationriboviz 2 is freely available at github.com/riboviz/riboviz.

Highlights

Ribo-seq quantifies the ‘translatome’ of actively translated RNAs in cells (Ingolia et al, 2009)
We present riboviz 2, an updated riboviz package, for the comprehensive transcript-centric analysis and visualization of Ribo-seq data. riboviz 2 includes an analysis workflow built on the Nextflow workflow management system for end-to-end processing of Ribo-seq data. riboviz 2 has been extensively tested on diverse species and library preparation strategies, including multiplexed samples. riboviz 2 is flexible and uses open, documented file formats, allowing users to integrate new analyses with the pipeline
Ribo-seq combines high-throughput sequencing with nuclease footprinting of ribosomes to identify the location of ribosomes across the transcriptome at codon-level resolution

Summary

Introduction

Ribo-seq quantifies the ‘translatome’ of actively translated RNAs in cells (Ingolia et al, 2009). Ribo-seq combines high-throughput sequencing with nuclease footprinting of ribosomes to identify the location of ribosomes across the transcriptome at codon-level resolution. Ribo-seq is often combined with RNA-seq to quantify post-transcriptional regulation and enables quantitative mechanistic insight into the movement of ribosomes along RNA. Specialized pipelines are needed for Ribo-seq data, covering preprocessing, read mapping, gene-specific and codon-specific quantification and other downstream analyses (Li et al, 2020). We previously developed riboviz as an analysis and visualization framework for Ribo-seq data (Carja et al, 2017). We present a significantly expanded and reworked version: riboviz 2

Materials and methods

New features and advantages

Data Availability Statement