DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics
DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics
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DOI：
10.1021/acs.jproteome.1c00123
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发表时间：
2021-06-21
影响因子：
4.4
通讯作者：
Rost, Hannes
中科院分区：
文献类型：
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作者：
Bichmann, Leon;Gupta, Shubham;Rost, Hannes
数据独立采集（DIA）正在成为生物医学质谱分析的主要方法。与数据依赖采集（DDA）相比，其主要优点包括更高的再现性和灵敏度以及更大的动态范围。然而，数据分析是复杂的，在处理大规模数据集时往往需要专业知识。在这里，我们介绍了DIAproteomics，这是一个多功能、自动化、高通量的流水线，在Nextflow工作流管理系统中实现，允许人们在不同的计算基础设施上轻松处理蛋白质组学和肽组学DIA数据集。核心组件是完善的工具，如用于DIA谱库搜索的OpenSwathWorkflow和用于错误发现率评估的PyProphet。此外，它还提供了从现有DDA数据生成光谱库的选项，并进行保留时间和色谱校准。输出包括在实验设计中预先定义的两两条件下折叠变化的统计后处理和计算的注释表和诊断可视化。DIAproteomics是一个记录良好的开源软件，在科学界的许可下可以在https://www上获得。openms.de / diaprotcoinics /。
Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https://www. openms.de/diaprotcoinics/.