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Updated: Aug 12, 2025

Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry
Published on: April 4, 2018
MSPypeline: a python package for streamlined data analysis of mass spectrometry-based proteomics
Simon Heming1, Pauline Hansen1,2, Artyom Vlasov1
1Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
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 Bioinformatics Advances online.
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