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PIONEER:用于生成 DIA-MS 数据高质量光谱库的管道。

PIONEER: Pipeline for Generating High-Quality Spectral Libraries for DIA-MS Data.

机构信息

ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia.

出版信息

Curr Protoc. 2021 Mar;1(3):e69. doi: 10.1002/cpz1.69.

Abstract

Data-independent-acquisition mass spectrometry (DIA-MS) is a state-of-the-art proteomic technique for high-throughput identification and quantification of peptides and proteins. Interpretation of DIA-MS data relies on the use of a spectral library, which is optimally created from data acquired from the same samples in data-dependent acquisition (DDA) mode. As DIA-MS quantification relies on the spectral libraries, having a high-quality, non-redundant, and comprehensive spectral library is essential. This article describes the major steps for creating a high-quality spectral library using a combination of multiple complementary search engines. We discuss appropriate strategies to control the false discovery rate for the final spectral library as a result of merging multiple searches. © 2021 The Authors Current Protocols © 2021 Wiley Periodicals LLC. Basic Protocol 1: Searching DDA-MS files with multiple search engines Basic Protocol 2: Merging results from multiple search engines Basic Protocol 3: Creating spectral libraries from merged results Alternate Protocol: Using CLI for automating tasks Support Protocol: Creating concatenated FASTA files.

摘要

数据非依赖性采集质谱(DIA-MS)是一种用于高通量鉴定和定量肽和蛋白质的最新蛋白质组学技术。DIA-MS 数据的解释依赖于光谱库的使用,该光谱库最优化地从数据依赖采集(DDA)模式下从相同样本中获取的数据创建。由于 DIA-MS 定量依赖于光谱库,因此拥有高质量、非冗余和全面的光谱库至关重要。本文描述了使用多种互补搜索引擎创建高质量光谱库的主要步骤。我们讨论了控制由于合并多个搜索而导致最终光谱库的错误发现率的适当策略。©2021 作者 当前协议 ©2021 威利在线图书馆。基本方案 1:使用多个搜索引擎搜索 DDA-MS 文件 基本方案 2:合并来自多个搜索引擎的结果 基本方案 3:从合并的结果创建光谱库 备选方案:使用 CLI 自动化任务 支持方案:创建串联的 FASTA 文件。

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