ArticleJournal of the American Society for Mass Spectrometry2018
Rapid Assessment of Contaminants and Interferences in Mass Spectrometry Data Using Skyline.
Article in Journal of the American Society for Mass Spectrometry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Analysis of FAIMS for the study of affinity-purified protein complexes using the orbitrap ascend tribrid mass spectrometer.Molecular omics · 2025Article
- Microflow Liquid Chromatography Coupled to Multinozzle Electrospray Ionization for Improved Lipidomics Coverage of 3D Clear Cell Renal Cell Carcinoma.Analytical chemistry · 2025Article
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- Challenges of MS-based small extracellular vesicles proteomics.Journal of extracellular vesicles · 2024Review
- Optimized Automated Workflow for BioID Improves Reproducibility and Identification of Protein-Protein Interactions.Journal of proteome research · 2024Article
- A Framework for Quality Control in Quantitative Proteomics.Journal of proteome research · 2024Article
- Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer.Journal of biomolecular techniques : JBT · 2024Article
- A framework for quality control in quantitative proteomics.bioRxiv : the preprint server for biology · 2024Article
- Benchmarking of Two Peptide Clean-Up Protocols: SP2 and Ethyl Acetate Extraction for Sodium Dodecyl Sulfate or Polyethylene Glycol Removal from Plant Samples before LC-MS/MS.International journal of molecular sciences · 2023Article
- Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics.Metabolites · 2023Article
- Lipidomics Workflow for Analyzing Lipid Profiles Using Multiple Reaction Monitoring (MRM) in Liver Homogenate of Mice with Non-alcoholic Steatohepatitis (NASH).Bio-protocol · 2023Article
- Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics.Journal of proteome research · 2022Article
- Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Identification and characterization of hADSC-derived exosome proteins from different isolation methods.Journal of cellular and molecular medicine · 2021Article
- Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics.Journal of proteome research · 2020Article
- DO-MS: Data-Driven Optimization of Mass Spectrometry Methods.Journal of proteome research · 2019Article
- SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses.Journal of proteome research · 2019Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g., detergents) necessitating a variety of sample cleanup procedures. Efforts to understand and mitigate sample contamination are a continual source of disruption with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, I developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows rapid assessment of sample integrity and indicates potential sources of contamination. Graphical Abstract ᅟ.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.