Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics
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Abstract
Mass spectrometry-based proteomics is constantly challenged by the presence of contaminant background signals. In particular, protein contaminants from reagents and sample handling are almost impossible to avoid. For data-dependent acquisition (DDA) proteomics, an exclusion list can be used to reduce the influence of protein contaminants. However, protein contamination has not been evaluated and is rarely addressed in data-independent acquisition (DIA). How protein contaminants influence proteomic data is also unclear. In this study, we established new protein contaminant FASTA and spectral libraries that are applicable to all proteomic workflows and evaluated the impact of protein contaminants on both DDA and…
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Topics
Keywords
- Workflow
- Proteomics
- Contamination
- Computer science
- Mass spectrometry
- Quantitative proteomics
- Computational biology
- Data science
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