A hierarchical statistical modeling approach to analyze proteomic isobaric tag for relative and absolute quantitation data

Bioinformatics
Cong ZhouAnthony D Whetton

Abstract

Isobaric tag for relative and absolute quantitation (iTRAQ) is a widely used method in quantitative proteomics. A robust data analysis strategy is required to determine protein quantification reliability, i.e. changes due to biological regulation rather than technical variation, so that proteins that are differentially expressed can be identified. Samples were created by mixing 5, 10, 15 and 20 μg Escherichia coli cell lysate with 100 μg of cell lysate from mouse, corresponding to expected relative fold changes of one for mouse proteins and from 0.25 to 4 for E.coli proteins. Relative quantification was carried out using eight channel isobaric tagging with iTRAQ reagent, and proteins were identified using a TripleTOF 5600 mass spectrometer. Technical variation inherent in this iTRAQ dataset was systematically investigated. A hierarchical statistical model was developed to use quantitative information at peptide level and protein level simultaneously to estimate variation present in each individual peptide and protein. A novel data analysis strategy for iTRAQ, denoted in short as WHATraq, was subsequently proposed with its performance evaluated by the proportion of E.coli proteins that are successfully identified as differential...Continue Reading

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Citations

Jan 28, 2016·International Journal of Cancer. Journal International Du Cancer·Matthew R RussellRobert L J Graham
Dec 28, 2016·Molecular Plant-microbe Interactions : MPMI·Flor E AcevedoGary Felton
Jun 8, 2017·Insect Biochemistry and Molecular Biology·Flor E AcevedoGary W Felton
Aug 14, 2019·Journal of Proteome Research·Bethany GearyAnthony D Whetton
Jul 28, 2016·Journal of Proteome Research·Ana Martinez-ValJavier Munoz

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