Title

Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC-MS/MS

UMMS Affiliation

Program in Molecular Medicine

Publication Date

11-6-2015

Document Type

Article

Disciplines

Amino Acids, Peptides, and Proteins | Biochemistry | Chemistry | Molecular Biology

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.

Keywords

Data-independent acquisition, SWATH, interference removal, mass spectrometry, multivariate outlier detection, peptides, quantification

DOI of Published Version

10.1021/acs.jproteome.5b00394

Source

J Proteome Res. 2015 Nov 6;14(11):4581-93. doi: 10.1021/acs.jproteome.5b00394. Epub 2015 Oct 14. Link to article on publisher's site

Journal/Book/Conference Title

Journal of proteome research

Related Resources

Link to Article in PubMed

PubMed ID

26412574

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