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A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows
- Source :
- J Proteome Res
- Publication Year :
- 2021
-
Abstract
- The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.
- Subjects :
- Lossless compression
Ions
business.industry
Computer science
Dynamic range
General Chemistry
Biochemistry
Lipids
Mass Spectrometry
Article
Computational science
Workflow
Software
Ion Mobility Spectrometry
Preprocessor
Humans
Data-independent acquisition
business
Smoothing
Interpolation
Data compression
Chromatography, Liquid
Subjects
Details
- ISSN :
- 15353907
- Volume :
- 21
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Journal of proteome research
- Accession number :
- edsair.doi.dedup.....a69d57ad21949f90d6853c437231014c