de Botton Institute for Protein Profiling, The Nancy and Stephen Grand Israel National Center for Personalized Medicine, Weizmann Institute of Science, Rehovot 76100, Israel.
Ilana and Pascal Mantoux Institute for Bioinformatics, The Nancy and Stephen Grand Israel National Center for Personalized Medicine, Weizmann Institute of Science, Rehovot 76100, Israel.
J Proteome Res. 2021 Apr 2;20(4):2098-2104. doi: 10.1021/acs.jproteome.0c00956. Epub 2021 Mar 3.
Every laboratory performing mass-spectrometry-based proteomics strives to generate high-quality data. Among the many factors that impact the outcome of any experiment in proteomics is the LC-MS system performance, which should be monitored within each specific experiment and also long term. This process is termed quality control (QC). We present an easy-to-use tool that rapidly produces a visual, HTML-based report that includes the key parameters needed to monitor the LC-MS system performance, with a focus on monitoring the performance within an experiment. The tool, named RawBeans, generates a report for individual files or for a set of samples from a whole experiment. We anticipate that it will help proteomics users and experts evaluate raw data quality independent of data processing. The tool is available at https://bitbucket.org/incpm/prot-qc/downloads. The mass-spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD022816.
每个进行基于质谱的蛋白质组学研究的实验室都努力生成高质量的数据。在影响蛋白质组学实验结果的众多因素中，LC-MS 系统性能是一个重要因素，应在每个特定实验中以及长期进行监测。这一过程被称为质量控制（QC）。我们介绍了一个易于使用的工具，它可以快速生成一个基于 HTML 的可视化报告，其中包含了监测 LC-MS 系统性能所需的关键参数，重点是监测实验中的性能。该工具名为 RawBeans，可针对单个文件或整个实验中的一组样本生成报告。我们预计它将帮助蛋白质组学用户和专家在不进行数据处理的情况下独立评估原始数据质量。该工具可在 https://bitbucket.org/incpm/prot-qc/downloads 获得。质谱蛋白质组学数据已通过 PRIDE 合作伙伴存储库存入 ProteomeXchange 联盟，数据集标识符为 PXD022816。
