title: Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC-MS/MS.
abstract: Data-independent acquisition LC-MS/MS techniques complement supervised methods for peptide quantification. However, due to the wide precursor isolation windows, these techniques are prone to interference at the fragment ion level, which, in turn, is detrimental for accurate quantification. The nonoutlier fragment ion (NOFI) ranking algorithm has been developed to assign low priority to fragment ions affected by interference. By using the optimal subset of high-priority fragment ions, these interfered fragment ions are effectively excluded from quantification. NOFI represents each fragment ion as a vector of four dimensions related to chromatographic and MS fragmentation attributes and applies multivariate outlier detection techniques. Benchmarking conducted on a well-defined quantitative data set (i.e., the SWATH Gold Standard) indicates that NOFI on average is able to accurately quantify 11-25% more peptides than the commonly used Top-N library intensity ranking method. The sum of the area of the Top3-5 NOFIs produces similar coefficients of variation as compared to that with the library intensity method but with more accurate quantification results. On a biologically relevant human dendritic cell digest data set, NOFI properly assigns low-priority ranks to 85% of annotated interferences, resulting in sensitivity values between 0.92 and 0.80, against 0.76 for the Spectronaut interference detection algorithm.
authors.affiliation: Life Sciences Mass Spectrometry, School of Pharmaceutical Sciences, University of Geneva, University of Lausanne , CH-1211 Geneva 4, Switzerland.|Proteome Informatics Group, SIB Swiss Institute of Bioinformatics , CH-1211 Geneva 4, Switzerland.
authors.forename: Aivett
authors.initials: A
authors.lastname: Bilbao
authors.affiliation: Life Sciences Mass Spectrometry, School of Pharmaceutical Sciences, University of Geneva, University of Lausanne , CH-1211 Geneva 4, Switzerland.
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Life Sciences Mass Spectrometry, School of Pharmaceutical Sciences, University of Geneva, University of Lausanne , CH-1211 Geneva 4, Switzerland.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Varesio
authors.affiliation: Program in Molecular Medicine, University of Massachusetts Medical School , Worcester, Massachusetts 01605, United States.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Luban
authors.affiliation: Program in Molecular Medicine, University of Massachusetts Medical School , Worcester, Massachusetts 01605, United States.
authors.forename: Caterina
authors.initials: C
authors.lastname: Strambio-De-Castillia
authors.affiliation: Proteome Informatics Group, SIB Swiss Institute of Bioinformatics , CH-1211 Geneva 4, Switzerland.|Faculty of Sciences, University of Geneva , CH-1211 Geneva 4, Switzerland.
authors.forename: Frédérique
authors.initials: F
authors.lastname: Lisacek
authors.affiliation: Life Sciences Mass Spectrometry, School of Pharmaceutical Sciences, University of Geneva, University of Lausanne , CH-1211 Geneva 4, Switzerland.
authors.forename: Gérard
authors.initials: G
authors.lastname: Hopfgartner
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D019985:Benchmarking; D002853:Chromatography, Liquid / Q000379:methods*; D003713:Dendritic Cells / Q000737:chemistry; D006367:HeLa Cells; D006801:Humans; D007477:Ions; D008969:Molecular Sequence Data; D010446:Peptide Fragments / Q000032:analysis*; D061251:Primary Cell Culture; D059748:Proteolysis; D020543:Proteome / Q000032:analysis* / Q000737:chemistry; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D007477:Ions; D010446:Peptide Fragments; D020543:Proteome
keywords: Data-independent acquisition; SWATH; interference removal; mass spectrometry; multivariate outlier detection; peptides; quantification