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Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 2.1.

Eric W Deutsch1, Christopher M Overall2, Jennifer E Van Eyk3

  • 1Institute for Systems Biology , 401 Terry Avenure North, Seattle, Washington 98109, United States.

Journal of Proteome Research
|August 5, 2016
PubMed
Summary
This summary is machine-generated.

The Human Proteome Project (HPP) developed mass spectrometry data interpretation guidelines to ensure data quality and comparability. These guidelines standardize HPP data submission and analysis for reliable protein identification results.

Keywords:
Human Proteome Projectalternative protein matchesfalse-discovery ratesguidelinesmass spectrometrystandards

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Area of Science:

  • Proteomics
  • Biochemistry
  • Data Science

Background:

  • Data-rich research initiatives require robust quality control for data interpretation and analysis comparability.
  • The Human Proteome Project (HPP) within the Human Proteome Organization (HUPO) identified a need for standardized data handling procedures.

Purpose of the Study:

  • To establish clear guidelines for interpreting and reporting mass spectrometry data within the HPP.
  • To ensure the quality, comparability, and reliability of protein identification data contributed to the HPP.

Main Methods:

  • Developed through broad community consultation, the guidelines comprise a one-page checklist of 15 essential points.
  • Detailed explanations of each guideline element are provided to support authors and reviewers.
  • Guidelines cover data submission to mass spectrometry repositories, error analysis presentation, and evidence for novel protein detection.

Main Results:

  • A comprehensive set of 15 mass spectrometry data interpretation guidelines for the HPP has been established.
  • The guidelines provide specific directions for data submission, error analysis, and validation of novel protein identifications.
  • The developed guidelines aim to enhance the integrity and reproducibility of HPP research.

Conclusions:

  • The HPP data interpretation guidelines are crucial for maintaining high standards in proteomic research.
  • These guidelines facilitate consistent data reporting and analysis across HPP contributions.
  • The presented guidelines are intended for adoption by the broader scientific community for discussion and refinement.