National Security Directorate , Pacific Northwest National Laboratory , 902 Battelle Boulevard , Richland , Washington 99354 , United States.
Earth & Biological Sciences Directorate , Pacific Northwest National Laboratory , 902 Battelle Boulavard , Richland , Washington 99354 , United States.
J Proteome Res. 2019 Mar 1;18(3):1418-1425. doi: 10.1021/acs.jproteome.8b00760. Epub 2019 Jan 28.
Prior to statistical analysis of mass spectrometry (MS) data, quality control (QC) of the identified biomolecule peak intensities is imperative for reducing process-based sources of variation and extreme biological outliers. Without this step, statistical results can be biased. Additionally, liquid chromatography-MS proteomics data present inherent challenges due to large amounts of missing data that require special consideration during statistical analysis. While a number of R packages exist to address these challenges individually, there is no single R package that addresses all of them. We present pmartR, an open-source R package, for QC (filtering and normalization), exploratory data analysis (EDA), visualization, and statistical analysis robust to missing data. Example analysis using proteomics data from a mouse study comparing smoke exposure to control demonstrates the core functionality of the package and highlights the capabilities for handling missing data. In particular, using a combined quantitative and qualitative statistical test, 19 proteins whose statistical significance would have been missed by a quantitative test alone were identified. The pmartR package provides a single software tool for QC, EDA, and statistical comparisons of MS data that is robust to missing data and includes numerous visualization capabilities.
在进行质谱（MS）数据分析之前，必须对鉴定出的生物分子峰强度进行质量控制（QC），以减少基于过程的变异源和极端生物学离群值。如果不进行这一步骤，统计结果可能会出现偏差。此外，由于存在大量缺失数据，液相色谱-MS 蛋白质组学数据在统计分析过程中需要特别考虑，因此存在固有挑战。虽然有许多 R 包可以单独解决这些挑战，但没有一个 R 包可以解决所有这些挑战。我们提出了 pmartR，这是一个开源的 R 包，用于 QC（过滤和归一化）、探索性数据分析（EDA）、可视化和对缺失数据具有鲁棒性的统计分析。使用来自一项比较吸烟暴露与对照的小鼠研究的蛋白质组学数据进行的示例分析展示了该软件包的核心功能，并强调了处理缺失数据的能力。特别是，使用一种综合的定量和定性统计测试，确定了 19 种仅通过定量测试可能会错过的蛋白质，这些蛋白质具有统计学意义。pmartR 软件包为 MS 数据的 QC、EDA 和统计比较提供了一个单一的软件工具，该工具对缺失数据具有鲁棒性，并包含许多可视化功能。
