PDF(Pubmed)
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.
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.
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.
摘要：
核糖体谱分析是一种在转录组范围内研究翻译的强大技术。然而,确保良好的数据质量对于准确解释至关重要，确保分析是可重复的。我们引入了一个新的NextflowDSL2管道，riboseq-flow,设计用于核糖体谱分析实验的加工和全面质量控制。Riboseq-flow是用户友好的，多才多艺，坚持高标准的可重复性，可扩展性，便携性,版本控制和持续集成。它使用户能够有效地并行分析多个样本，并帮助他们根据自动生成的详细指标和可视化来评估数据的质量和实用性。Riboseq-flow可在https://github.com/iraisub/riboseq-flow获得。
核糖体谱分析是一种先进的方法，可提供细胞内整个RNA分子的蛋白质合成的详细视图。为确保此类研究的可靠性,高质量的数据和复制分析的能力至关重要。为了解决这个问题，我们展示了核糖序列流，NextflowDSL2构建的新工具，专门用于分析核糖体分析实验的数据。这条管道因其易用性而脱颖而出，灵活性,并致力于高再现性标准。它的设计可以同时处理多个样本，确保大规模研究的有效分析。此外，riboseq-flow自动生成详细的报告和视觉表示来评估数据质量，加强研究人员对他们实验的理解，并指导未来的决策。这个宝贵的资源可以在https://github.com/iraisub/riboseq-flow上免费访问。
核糖体谱分析是一种先进的方法，可提供细胞内整个RNA分子的蛋白质合成的详细视图。为确保此类研究的可靠性,高质量的数据和复制分析的能力至关重要。为了解决这个问题，我们展示了核糖序列流，NextflowDSL2构建的新工具，专门用于分析核糖体分析实验的数据。这条管道因其易用性而脱颖而出，灵活性,并致力于高再现性标准。它的设计可以同时处理多个样本，确保大规模研究的有效分析。此外，riboseq-flow自动生成详细的报告和视觉表示来评估数据质量，加强研究人员对他们实验的理解，并指导未来的决策。这个宝贵的资源可以在https://github.com/iraisub/riboseq-flow上免费访问。
