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MSPypeline: a python package for streamlined data analysis of mass spectrometry-based proteomics.
Heming, Simon; Hansen, Pauline; Vlasov, Artyom; Schwörer, Florian; Schaumann, Stephen; Frolovaite, Paulina; Lehmann, Wolf-Dieter; Timmer, Jens; Schilling, Marcel; Helm, Barbara; Klingmüller, Ursula.
Afiliação
  • Heming S; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Hansen P; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Vlasov A; Institute for Physics and CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg 79104, Germany.
  • Schwörer F; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Schaumann S; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Frolovaite P; Institute for Physics and CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg 79104, Germany.
  • Lehmann WD; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Timmer J; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Schilling M; Institute for Physics and CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg 79104, Germany.
  • Helm B; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
  • Klingmüller U; Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.
Bioinform Adv ; 2(1): vbac004, 2022.
Article em En | MEDLINE | ID: mdl-36699356
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article