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Related Concept Videos

Proteomics01:33

Proteomics

10.2K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

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ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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Dissecting Multi-protein Signaling Complexes by Bimolecular Complementation Affinity Purification BiCAP
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Proteomics Quality Control: Quality Control Software for MaxQuant Results.

Chris Bielow1,2, Guido Mastrobuoni1, Stefan Kempa1,2

  • 1Max-Delbrück-Centrum for Molecular Medicine Berlin , Robert-Rössle-Straße 10, 13125 Berlin, Germany.

Journal of Proteome Research
|December 15, 2015
PubMed
Summary
This summary is machine-generated.

Automated quality control for mass spectrometry proteomics data is essential. PTXQC is a new R-based pipeline that provides automated quality metrics and reports for MaxQuant software, improving data reliability.

Keywords:
MaxQuantPTXQCquality control

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Area of Science:

  • Proteomics
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Mass spectrometry-based proteomics generates large datasets requiring robust quality control.
  • Automated quality control (QC) and quality analysis (QA) are critical for detecting bias and ensuring consistency in high-throughput proteomics data.

Purpose of the Study:

  • To develop an automated R-based QC pipeline for bottom-up liquid chromatography-mass spectrometry (LC-MS) data processed by MaxQuant.
  • To provide a comprehensive set of QC metrics with automated scoring for improved data analysis.

Main Methods:

  • Development of the Proteomics Quality Control (PTXQC) R package.
  • Integration of automated scoring functions and heatmap visualization for QC reports.
  • Inclusion of metrics for various experimental designs (SILAC, TMT, label-free) and MaxQuant's Match-between-runs (MBR).

Main Results:

  • PTXQC generates detailed QC reports with automated scores and an overview heatmap.
  • The pipeline supports diverse experimental designs and enhances the assessment of MBR functionality.
  • PTXQC is user-friendly, easy to install, and the first software to process MaxQuant result tables.

Conclusions:

  • PTXQC offers a powerful, automated solution for quality control in mass spectrometry proteomics.
  • The software aids instrument operators and scientists in ensuring data quality and reliability.
  • PTXQC is freely available, promoting wider adoption and standardization in proteomics data analysis.