{Reference Type}: Journal Article
{Title}: Riboseq-flow: A streamlined, reliable pipeline for ribosome profiling data analysis and quality control.
{Author}: Iosub IA;Wilkins OG;Ule J;
{Journal}: Wellcome Open Res
{Volume}: 9
{Issue}: 0
{Year}: 2024
暂无{DOI}: 10.12688/wellcomeopenres.21000.1
{Abstract}: Ribosome profiling is a powerful technique to study translation at a transcriptome-wide level. However, ensuring good data quality is paramount for accurate interpretation, as is ensuring that the analyses are reproducible. We introduce a new Nextflow DSL2 pipeline, riboseq-flow, designed for processing and comprehensive quality control of ribosome profiling experiments. Riboseq-flow is user-friendly, versatile and upholds high standards in reproducibility, scalability, portability, version control and continuous integration. It enables users to efficiently analyse multiple samples in parallel and helps them evaluate the quality and utility of their data based on the detailed metrics and visualisations that are automatically generated. Riboseq-flow is available at https://github.com/iraiosub/riboseq-flow.<BR>Ribosome profiling is a cutting-edge method that provides a detailed view of protein synthesis across the entire set of RNA molecules within cells. To ensure the reliability of such studies, high-quality data and the ability to replicate analyses are crucial. To address this, we present riboseq-flow, a new tool built with Nextflow DSL2, tailored for analysing data from ribosome profiling experiments. This pipeline stands out for its ease of use, flexibility, and commitment to high reproducibility standards. It's designed to handle multiple samples simultaneously, ensuring efficient analysis for large-scale studies. Moreover, riboseq-flow automatically generates detailed reports and visual representations to assess the data quality, enhancing researchers' understanding of their experiments and guiding future decisions. This valuable resource is freely accessible at https://github.com/iraiosub/riboseq-flow.