MSPypeline：一个用于简化基于质谱的蛋白质组学数据分析的Python软件包。
MSPypeline: a python package for streamlined data analysis of mass spectrometry-based proteomics.
作者信息
Heming Simon, Hansen Pauline, Vlasov Artyom, Schwörer Florian, Schaumann Stephen, Frolovaitė Paulina, Lehmann Wolf-Dieter, Timmer Jens, Schilling Marcel, Helm Barbara, Klingmüller Ursula
机构信息
Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
Institute for Physics and CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg 79104, Germany.
出版信息
Bioinform Adv. 2022 Jan 17;2(1):vbac004. doi: 10.1093/bioadv/vbac004. eCollection 2022.
SUMMARY
Mass spectrometry-based proteomics is increasingly employed in biology and medicine. To generate reliable information from large datasets and ensure comparability of results, it is crucial to implement and standardize the quality control of the raw data, the data processing steps and the statistical analyses. MSPypeline provides a platform for importing MaxQuant output tables, generating quality control reports, data preprocessing including normalization and performing exploratory analyses by statistical inference plots. These standardized steps assess data quality, provide customizable figures and enable the identification of differentially expressed proteins to reach biologically relevant conclusions.
AVAILABILITY AND IMPLEMENTATION
The source code is available under the MIT license at https://github.com/siheming/mspypeline with documentation at https://mspypeline.readthedocs.io. Benchmark mass spectrometry data are available on ProteomeXchange (PXD025792).
SUPPLEMENTARY INFORMATION
Supplementary data are available at online.
摘要
基于质谱的蛋白质组学在生物学和医学中的应用越来越广泛。为了从大型数据集中生成可靠信息并确保结果的可比性，对原始数据、数据处理步骤和统计分析实施并标准化质量控制至关重要。MSPypeline提供了一个平台，用于导入MaxQuant输出表、生成质量控制报告、进行包括归一化在内的数据预处理，并通过统计推断图进行探索性分析。这些标准化步骤评估数据质量，提供可定制的图表，并能够识别差异表达的蛋白质，从而得出具有生物学意义的结论。
可用性和实现方式
补充信息
补充数据可在网上获取。
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