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DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics

Author

Listed:
  • Mukul K. Midha

    (Institute for Systems Biology)

  • David S. Campbell

    (Institute for Systems Biology)

  • Charu Kapil

    (Institute for Systems Biology)

  • Ulrike Kusebauch

    (Institute for Systems Biology)

  • Michael R. Hoopmann

    (Institute for Systems Biology)

  • Samuel L. Bader

    (Institute for Systems Biology)

  • Robert L. Moritz

    (Institute for Systems Biology)

Abstract

Data-independent acquisition (DIA) mass spectrometry, also known as Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH), is a popular label-free proteomics strategy to comprehensively quantify peptides/proteins utilizing mass spectral libraries to decipher inherently multiplexed spectra collected linearly across a mass range. Although there are many spectral libraries produced worldwide, the quality control of these libraries is lacking. We present the DIALib-QC (DIA library quality control) software tool for the systematic evaluation of a library’s characteristics, completeness and correctness across 62 parameters of compliance, and further provide the option to improve its quality. We demonstrate its utility in assessing and repairing spectral libraries for correctness, accuracy and sensitivity.

Suggested Citation

  • Mukul K. Midha & David S. Campbell & Charu Kapil & Ulrike Kusebauch & Michael R. Hoopmann & Samuel L. Bader & Robert L. Moritz, 2020. "DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18901-y
    DOI: 10.1038/s41467-020-18901-y
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    Cited by:

    1. Yi Yang & Qun Fang, 2024. "Prediction of glycopeptide fragment mass spectra by deep learning," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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