DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics-Reference-Cited by-同舟云学术

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

Published:2020-10-16 Issue:1 Volume:11 Page:
ISSN:2041-1723
Container-title:Nature Communications
language:en
Short-container-title:Nat Commun

Author:

Midha Mukul K.^ORCID,Campbell David S.,Kapil Charu^ORCID,Kusebauch Ulrike^ORCID,Hoopmann Michael R.^ORCID,Bader Samuel L.,Moritz Robert L.^ORCID

Abstract

AbstractData-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.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

Link

https://www.nature.com/articles/s41467-020-18901-y.pdf

Reference23 articles.

1. Aebersold, R. & Mann, M. Mass-spectrometric exploration of proteome structure and function. Nature 537, 347–355 (2016).

2. Kusebauch, U. et al. Human SRMAtlas: a resource of targeted assays to quantify the complete human proteome. Cell 166, 766–778 (2016).

3. Venable, J. D., Dong, M. Q., Wohlschlegel, J., Dillin, A. & Yates, J. R. Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat. Methods 1, 39–45 (2004).

4. Gillet, L. C. et al. Targeted data extraction of the MS/MS spectratra generated by data-independent a generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell. Proteom. 11, https://doi.org/10.1074/mcp.O111.016717 (2012).

5. Weisbrod, C. R., Eng, J. K., Hoopmann, M. R., Baker, T. & Bruce, J. E. Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification. J. Proteome Res. 11, 1621–1632 (2012).

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