管道(软件)
工作流程
计算机科学
吞吐量
协议(科学)
数据采集
数据挖掘
匹配(统计)
实时计算
数据库
操作系统
医学
统计
替代医学
数学
病理
无线
作者
Leon Bichmann,Shubham Gupta,Hannes Röst
出处
期刊:Methods in molecular biology
日期:2024-01-01
卷期号:: 77-88
标识
DOI:10.1007/978-1-0716-3646-6_4
摘要
In recent years, data-independent acquisition (DIA) has emerged as a powerful analysis method in biological mass spectrometry (MS). Compared to the previously predominant data-dependent acquisition (DDA), it offers a way to achieve greater reproducibility, sensitivity, and dynamic range in MS measurements. To make DIA accessible to non-expert users, a multifunctional, automated high-throughput pipeline DIAproteomics was implemented in the computational workflow framework "Nextflow" ( https://nextflow.io ). This allows high-throughput processing of proteomics and peptidomics DIA datasets on diverse computing infrastructures. This chapter provides a short summary and usage protocol guide for the most important modes of operation of this pipeline regarding the analysis of peptidomics datasets using the command line. In brief, DIAproteomics is a wrapper around the OpenSwathWorkflow and relies on either existing or ad-hoc generated spectral libraries from matching DDA runs. The OpenSwathWorkflow extracts chromatograms from the DIA runs and performs chromatographic peak-picking. Further downstream of the pipeline, these peaks are scored, aligned, and statistically evaluated for qualitative and quantitative differences across conditions depending on the user's interest. DIAproteomics is open-source and available under a permissive license. We encourage the scientific community to use or modify the pipeline to meet their specific requirements.
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