Dataset Information
MSPypeline: a python package for streamlined data analysis of mass spectrometry-based proteomics.
Ontology highlight
ABSTRACT: 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.
SUBMITTER: Heming S
PROVIDER: S-EPMC9710650 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
MSPypeline: a python package for streamlined data analysis of mass spectrometry-based proteomics.
Bioinformatics advances 20220117 1
<h4>Summary</h4>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 explorator ...[more]
