期刊
BMC BIOINFORMATICS
卷 19, 期 -, 页码 -出版社
BIOMED CENTRAL LTD
DOI: 10.1186/s12859-018-2075-8
关键词
Mass spectrometry; SRM; Validation biomarkers; Technical variability; Experimental design; Variance component analysis
类别
资金
- Agence Nationale pour la Recherche (ANR) [2010 BLAN 0313]
Background: In the field of biomarker validation with mass spectrometry, controlling the technical variability is a critical issue. In selected reaction monitoring (SRM) measurements, this issue provides the opportunity of using variance component analysis to distinguish various sources of variability. However, in case of unbalanced data (unequal number of observations in all factor combinations), the classical methods cannot correctly estimate the various sources of variability, particularly in presence of interaction. The present paper proposes an extension of the variance component analysis to estimate the various components of the variance, including an interaction component in case of unbalanced data. Results: We applied an experimental design that uses a serial dilution to generate known relative protein concentrations and estimated these concentrations by two processing algorithms, a classical and a more recent one. The extended method allowed estimating the variances explained by the dilution and the technical process by each algorithm in an experiment with 9 proteins: L-FABP, 14.3.3 sigma, Calgi, Def. A6, Villin, Calmo, I-FABP, Peroxi-5, and S100A14. Whereas, the recent algorithm gave a higher dilution variance and a lower technical variance than the classical one in two proteins with three peptides (L-FABP and Villin), there were no significant difference between the two algorithms on all proteins. Conclusions: The extension of the variance component analysis was able to estimate correctly the variance components of protein concentration measurement in case of unbalanced design.
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