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Data-Driven Optimization of DIA Mass-Spectrometry by DO-MS

View ORCID ProfileGeorg Wallmann, View ORCID ProfileAndrew Leduc, View ORCID ProfileNikolai Slavov
doi: https://doi.org/10.1101/2023.02.02.526809
Georg Wallmann
1Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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Andrew Leduc
1Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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Nikolai Slavov
1Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
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  • For correspondence: nslavov@northeastern.edu
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Abstract

Mass-spectrometry (MS) enables specific and accurate quantification of proteins with ever increasing throughput and sensitivity. Maximizing this potential of MS requires optimizing data acquisition parameters and performing efficient quality control for large datasets. To facilitate these objectives, we extended the DO-MS app (do-ms.slavovlab.net) to optimize and evaluate results from data independent acquisition (DIA) MS. The extension works with both label free and multiplexed DIA (plexDIA) and supports optimizations particularly relevant for single-cell proteomics. We demonstrate multiple use cases, including optimization of duty cycle methods, peptide separation, number of survey scans per duty cycle, and quality control of single-cell plexDIA data. DO-MS allows for interactive data display and generation of extensive reports, including publication quality figures, that can be easily shared. The source code is available at: github.com/SlavovLab/DO-MS.

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Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ∈ Data, code & protocols: do-ms.slavovlab.net

  • https://do-ms.slavovlab.net

  • https://github.com/SlavovLab/DO-MS

  • https://scp.slavovlab.net

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 03, 2023.
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Data-Driven Optimization of DIA Mass-Spectrometry by DO-MS
Georg Wallmann, Andrew Leduc, Nikolai Slavov
bioRxiv 2023.02.02.526809; doi: https://doi.org/10.1101/2023.02.02.526809
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Data-Driven Optimization of DIA Mass-Spectrometry by DO-MS
Georg Wallmann, Andrew Leduc, Nikolai Slavov
bioRxiv 2023.02.02.526809; doi: https://doi.org/10.1101/2023.02.02.526809

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