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Title: Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data [QC-ART: A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data]

Abstract

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility andmore » performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. In conclusion, we also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.« less

Authors:
 [1]; ORCiD logo [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]; ORCiD logo [1];  [1]; ORCiD logo [1];  [1]; ORCiD logo [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
Contributing Org.:
TEDDY Study Group
OSTI Identifier:
1471239
Report Number(s):
PNNL-SA-129934
Journal ID: ISSN 1535-9476
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Molecular and Cellular Proteomics
Additional Journal Information:
Journal Volume: 17; Journal Issue: 9; Journal ID: ISSN 1535-9476
Publisher:
American Society for Biochemistry and Molecular Biology
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 47 OTHER INSTRUMENTATION

Citation Formats

Stanfill, Bryan A., Nakayasu, Ernesto S., Bramer, Lisa M., Thompson, Allison M., Ansong, Charles K., Clauss, Therese R., Gritsenko, Marina A., Monroe, Matthew E., Moore, Ronald J., Orton, Daniel J., Piehowski, Paul D., Schepmoes, Athena A., Smith, Richard D., Webb-Robertson, Bobbie-Jo M., and Metz, Thomas O. Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data [QC-ART: A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data]. United States: N. p., 2018. Web. doi:10.1074/mcp.RA118.000648.
Stanfill, Bryan A., Nakayasu, Ernesto S., Bramer, Lisa M., Thompson, Allison M., Ansong, Charles K., Clauss, Therese R., Gritsenko, Marina A., Monroe, Matthew E., Moore, Ronald J., Orton, Daniel J., Piehowski, Paul D., Schepmoes, Athena A., Smith, Richard D., Webb-Robertson, Bobbie-Jo M., & Metz, Thomas O. Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data [QC-ART: A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data]. United States. doi:10.1074/mcp.RA118.000648.
Stanfill, Bryan A., Nakayasu, Ernesto S., Bramer, Lisa M., Thompson, Allison M., Ansong, Charles K., Clauss, Therese R., Gritsenko, Marina A., Monroe, Matthew E., Moore, Ronald J., Orton, Daniel J., Piehowski, Paul D., Schepmoes, Athena A., Smith, Richard D., Webb-Robertson, Bobbie-Jo M., and Metz, Thomas O. Mon . "Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data [QC-ART: A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data]". United States. doi:10.1074/mcp.RA118.000648. https://www.osti.gov/servlets/purl/1471239.
@article{osti_1471239,
title = {Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data [QC-ART: A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data]},
author = {Stanfill, Bryan A. and Nakayasu, Ernesto S. and Bramer, Lisa M. and Thompson, Allison M. and Ansong, Charles K. and Clauss, Therese R. and Gritsenko, Marina A. and Monroe, Matthew E. and Moore, Ronald J. and Orton, Daniel J. and Piehowski, Paul D. and Schepmoes, Athena A. and Smith, Richard D. and Webb-Robertson, Bobbie-Jo M. and Metz, Thomas O.},
abstractNote = {Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. In conclusion, we also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.},
doi = {10.1074/mcp.RA118.000648},
journal = {Molecular and Cellular Proteomics},
issn = {1535-9476},
number = 9,
volume = 17,
place = {United States},
year = {2018},
month = {4}
}

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