PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Journal Article · Tue Jul 16 00:00:00 EDT 2024 · Journal of the American Society for Mass Spectrometry

DOI:https://doi.org/10.1021/jasms.4c00146· OSTI ID:2438468

Harrison, Andrea ^[1]; Eder, Josie G. ^[2]; Lalli, Priscila M. ^[2]; Munoz, Nathalie ^[3]; Gao, Yuqian ^[4]; Clendinen, Chaevien S. ^[1]; Orton, Daniel J. ^[2]; Zheng, Xueyun ^[2]; Williams, Sarah M. ^[1]; Couvillion, Sneha P. ^[2]; Chu, Rosalie K. ^[1]; Balasubramanian, Vimal K. ^[1]; Bhattacharjee, Arunima ^[1]; Anderton, Christopher R. ^[1]; Pomraning, Kyle R. ^[4]; Burnum-Johnson, Kristin E. ^[3]; Liu, Tao ^[2]; Kyle, Jennifer E. ^[2]; Bilbao, Aivett ^[3]

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1. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory (EMSL)
2. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
3. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory (EMSL); USDOE Agile BioFoundry, Emeryville, CA (United States)
4. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), Office of Workforce Development for Teachers & Scientists (WDTS)
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 2438468
• Alternate ID(s): OSTI ID: 2480313
• Report Number(s): PNNL-SA--197329
• Journal Information: Journal of the American Society for Mass Spectrometry, Journal Name: Journal of the American Society for Mass Spectrometry Journal Issue: 11 Vol. 35; ISSN 1044-0305
• Publisher: American Society for Mass Spectrometry
• Country of Publication: United States
• Language: English

Related Subjects

47 OTHER INSTRUMENTATION
algorithm
computational tool
data processing
data quality control
data-dependent acquisition
data-independent acquisition
ion mobility spectrometry
lipidomics
liquid chromatography
metabolomics
proteomics