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Avant-garde: an automated data-driven DIA data curation tool

by DeRuff, Katherine C. , Shulman, Nicholas , Carr, Steven A. , MacCoss, Michael J. , Krug, Karsten , MacLean, Brendan , Vaca Jacome, Alvaro Sebastian , Peckner, Ryan , Officer, Adam , Jaffe, Jacob D. , Christianson, Karen E.

in 631/114/2784 / 631/114/794 / 631/1647/296 / 631/45/475 / Automatic data collection systems / Automation / Avant-garde / Bioinformatics / Biological Microscopy / Biological Techniques / Biomedical and Life Sciences / Biomedical Engineering/Biotechnology / Cell Line / Computer applications / Data Analysis / Data Curation - methods / Data Science - methods / Datasets / HEK293 Cells / Humans / Inspection / Life Sciences / Mass spectrometry / Mass Spectrometry - methods / Mass spectroscopy / Methods / Optimization / Peptides / Peptides - analysis / Proteome - analysis / Proteomics / Proteomics - methods / Reproducibility of Results / Scientific imaging / Selectivity / Software / Spectroscopy / Visual signals

2020

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2020

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2020

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Journal Article

Avant-garde: an automated data-driven DIA data curation tool

DeRuff, Katherine C.,

Shulman, Nicholas,

Carr, Steven A.,

MacCoss, Michael J.,

Krug, Karsten,

MacLean, Brendan,

Vaca Jacome, Alvaro Sebastian,

Peckner, Ryan,

Officer, Adam,

Jaffe, Jacob D.,

Christianson, Karen E.

2020

Overview

Several challenges remain in data-independent acquisition (DIA) data analysis, such as to confidently identify peptides, define integration boundaries, remove interferences, and control false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. We present Avant-garde as a tool to refine DIA (and parallel reaction monitoring) data. Avant-garde uses a novel data-driven scoring strategy: signals are refined by learning from the dataset itself, using all measurements in all samples to achieve the best optimization. We evaluate the performance of Avant-garde using benchmark DIA datasets and show that it can determine the quantitative suitability of a peptide peak, and reach the same levels of selectivity, accuracy, and reproducibility as manual validation. Avant-garde is complementary to existing DIA analysis engines and aims to establish a strong foundation for subsequent analysis of quantitative mass spectrometry data. A computational tool, Avant-garde, automates refinement of data-independent acquisition mass spectrometry-based quantitative proteomics data.

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Publisher

Nature Publishing Group US,Nature Publishing Group

Subject

/ Automatic data collection systems

/ Automation

/ Avant-garde