RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution.
RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution.
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RiboFlow、RiboR 和 RiboPy：用于以读长分辨率分析核糖体分析数据的生态系统。
DOI：
10.1093/bioinformatics/btaa028
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Cenik,Can
中科院分区：
文献类型：
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作者：
Ozadam,Hakan;Geng,Michael;Cenik,Can
摘要核糖体占用测量能够估计蛋白质丰度并推断翻译机制。最近的研究表明，核糖体分析数据中的序列读取长度变化很大，并且携带关键信息。因此，数据分析需要计算和存储各种核糖体足迹长度的多个指标。我们开发了一个软件生态系统，包括一种名为“ribo”的新型高效二进制文件格式。 Ribo 文件存储按核糖体足迹长度分组的所有基本数据。用户可以使用我们处理原始核糖体分析测序数据的 RiboFlow 管道来组装 ribo 文件。 RiboFlow 具有高度可移植性和可定制性，可跨大量计算环境，并具有内置并行化功能。我们还开发了用于在 R (RiboR) 和 Python (RiboPy) 环境中写入和读取 ribo 文件的接口。使用 RiboR 和 RiboPy，用户可以有效地访问核糖体分析质量控制指标、生成基本图并进行分析。总之，这些组件创建了一个软件生态系统，供研究人员通过核糖体分析研究翻译。可用性和实施有关快速入门，请参阅 https://ribosomeprofiling.github.io。源代码、安装说明和文档链接可在 GitHub 上获取：https://github.com/ribosomeprofiling。补充信息补充数据可在 Bioinformaticsonline 上获取。
SummaryRibosome occupancy measurements enable protein abundance estimation and infer mechanisms of translation. Recent studies have revealed that sequence read lengths in ribosome profiling data are highly variable and carry critical information. Consequently, data analyses require the computation and storage of multiple metrics for a wide range of ribosome footprint lengths. We developed a software ecosystem including a new efficient binary file format named ‘ribo’. Ribo files store all essential data grouped by ribosome footprint lengths. Users can assemble ribo files using our RiboFlow pipeline that processes raw ribosomal profiling sequencing data. RiboFlow is highly portable and customizable across a large number of computational environments with built-in capabilities for parallelization. We also developed interfaces for writing and reading ribo files in the R (RiboR) and Python (RiboPy) environments. Using RiboR and RiboPy, users can efficiently access ribosome profiling quality control metrics, generate essential plots and carry out analyses. Altogether, these components create a software ecosystem for researchers to study translation through ribosome profiling.Availability and implementationFor a quickstart, please see https://ribosomeprofiling.github.io. Source code, installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling.Supplementary informationSupplementary data are available atBioinformaticsonline.