Michalik Stephan, Hammer Elke, Steil Leif, Salazar Manuela Gesell, Hentschker Christian, Surmann Kristin, Busch Larissa M, Sura Thomas, Völker Uwe
Department Functional Genomics, Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, MV 17475, Germany.
German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany.
Bioinformatics. 2025 Mar 4;41(3). doi: 10.1093/bioinformatics/btaf086.
Proteome studies frequently encounter challenges in down-stream data analysis due to limited bioinformatics resources, rapid data generation, and variations in analytical methods. To address these issues, we developed SpectroPipeR, an R package designed to streamline data analysis tasks and provide a comprehensive, standardized pipeline for Spectronaut® DIA-MS data. This novel package automates various analytical processes, including XIC plots, ID rate summary, normalization, batch and covariate adjustment, relative protein quantification, multivariate analysis, and statistical analysis, while generating interactive HTML reports for e.g. ELN systems.
The SpectroPipeR package (manual: https://stemicha.github.io/SpectroPipeR/) was written in R and is freely available on GitHub (https://github.com/stemicha/SpectroPipeR).
由于生物信息学资源有限、数据生成速度快以及分析方法的差异，蛋白质组学研究在下游数据分析中经常遇到挑战。为了解决这些问题，我们开发了SpectroPipeR，这是一个R包，旨在简化数据分析任务，并为Spectronaut® DIA-MS数据提供一个全面、标准化的流程。这个新颖的包自动化了各种分析过程，包括XIC图、鉴定率汇总、归一化、批次和协变量调整、相对蛋白质定量、多变量分析和统计分析，同时为例如电子实验室笔记本（ELN）系统生成交互式HTML报告。
SpectroPipeR包（手册：https://stemicha.github.io/SpectroPipeR/）用R编写，可在GitHub（https://github.com/stemicha/SpectroPipeR）上免费获取。
