PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data.
Andrea HarrisonJosie G EderPriscila M LalliNathalie MunozYuqian GaoChaevien S ClendinenDaniel J OrtonXueyun ZhengSarah M WilliamsSneha P CouvillionRosalie K ChuVimal K BalasubramanianArunima BhattacharjeeChristopher R AndertonKyle R PomraningKristin E Burnum-JohnsonTao LiuJennifer E KyleAivett BilbaoPublished in: Journal of the American Society for Mass Spectrometry (2024)
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, 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.
Keyphrases
- mass spectrometry
- liquid chromatography
- quality control
- gas chromatography
- deep learning
- high throughput
- capillary electrophoresis
- machine learning
- single cell
- high resolution
- high resolution mass spectrometry
- electronic health record
- high performance liquid chromatography
- big data
- tandem mass spectrometry
- data analysis
- low dose
- simultaneous determination
- artificial intelligence
- human health
- multiple sclerosis
- quantum dots
- molecular dynamics
- quality improvement
- label free