diaTracer enables spectrum-centric analysis of diaPASEF proteomics data
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View abstract on PubMed
Summary
This summary is machine-generated.diaTracer enhances data-independent acquisition (DIA) proteomics by enabling direct peptide identification and quantification from diaPASEF data. This computational tool improves accuracy and protein depth across diverse biological samples and experiments.
Area Of Science
- Proteomics
- Mass Spectrometry
- Computational Biology
Background
- Data-independent acquisition (DIA) is crucial for peptide and protein quantification.
- Ion mobility separation, like diaPASEF, enhances DIA accuracy and depth.
- Existing DIA tools may not fully leverage 3D data (m/z, RT, ion mobility).
Purpose Of The Study
- Introduce diaTracer, a computational tool for diaPASEF data analysis.
- Enable direct, library-free peptide identification and quantification.
- Demonstrate diaTracer's utility across various proteomics applications.
Main Methods
- Developed diaTracer for spectrum-centric, 3D peak tracing and feature detection.
- Generated "pseudo-MS/MS" spectra for direct analysis.
- Integrated diaTracer into the FragPipe computational platform.
Main Results
- Successfully identified and quantified peptides from diverse diaPASEF datasets (TNBC, CSF, plasma, phosphoproteomics, immunopeptidomics, spatial proteomics).
- Achieved unrestricted identification of post-translational modifications using open searches.
- Demonstrated improved quantification accuracy and protein depth.
Conclusions
- diaTracer provides a powerful, direct approach for analyzing diaPASEF data.
- The tool enhances peptide identification, quantification, and PTM analysis.
- diaTracer and FragPipe integration streamline complex proteomics workflows.
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