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蛋白质组学差异表达分析的综合套餐。

: A Comprehensive -Package for Proteomics Differential Expression Analysis.

机构信息

Functional Genomics Center Zurich (FGCZ)-University of Zurich/ETH Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.

Swiss Institute of Bioinformatics (SIB) Quartier Sorge-Batiment Amphipole, 1015 Lausanne, Switzerland.

出版信息

J Proteome Res. 2023 Apr 7;22(4):1092-1104. doi: 10.1021/acs.jproteome.2c00441. Epub 2023 Mar 20.

Abstract

Mass spectrometry is widely used for quantitative proteomics studies, relative protein quantification, and differential expression analysis of proteins. There is a large variety of quantification software and analysis tools. Nevertheless, there is a need for a modular, easy-to-use application programming interface in that transparently supports a variety of well principled statistical procedures to make applying them to proteomics data, comparing and understanding their differences easy. The package integrates essential steps of the mass spectrometry-based differential expression analysis workflow: quality control, data normalization, protein aggregation, statistical modeling, hypothesis testing, and sample size estimation. The package makes integrating new data formats easy. It can be used to model simple experimental designs with a single explanatory variable and complex experiments with multiple factors and hypothesis testing. The implemented methods allow sensitive and specific differential expression analysis. Furthermore, the package implements benchmark functionality that can help to compare data acquisition, data preprocessing, or data modeling methods using a gold standard data set. The application programmer interface of strives to be clear, predictable, discoverable, and consistent to make proteomics data analysis application development easy and exciting. Finally, the -package is available on GitHub https://github.com/fgcz/prolfqua, distributed under the MIT license. It runs on all platforms supported by the free software environment for statistical computing and graphics.

摘要

质谱广泛用于定量蛋白质组学研究、相对蛋白质定量和蛋白质差异表达分析。有各种各样的定量软件和分析工具。然而,我们需要一个模块化、易于使用的应用程序编程接口,该接口透明地支持各种有原则的统计程序,以便将它们应用于蛋白质组学数据,比较和理解它们的差异。prolfqua 包集成了基于质谱的差异表达分析工作流程的基本步骤:质量控制、数据标准化、蛋白质聚集、统计建模、假设检验和样本量估计。该包使新数据格式的集成变得容易。它可用于对具有单个解释变量的简单实验设计和具有多个因素和假设检验的复杂实验进行建模。所实现的方法允许进行敏感和特异性的差异表达分析。此外,该包实现了基准功能,可以使用黄金标准数据集帮助比较数据采集、数据预处理或数据建模方法。prolfqua 的应用程序编程接口旨在清晰、可预测、可发现和一致,使蛋白质组学数据分析应用程序的开发变得简单和令人兴奋。最后,-package 可在 GitHub https://github.com/fgcz/prolfqua 上获得,根据麻省理工学院的许可证分发。它在支持统计计算和图形的免费软件环境的所有平台上运行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd6/10088014/a0cdda1279ee/pr2c00441_0003.jpg

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