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A robust permutation test for quantitative SILAC proteomics experiments

Author(s): Hien D. Nguyen | Ian A. Wood | Michelle M. Hill

Journal: Journal of Integrated OMICS
ISSN 2182-0287

Volume: 2;
Issue: 2;
Start page: 80;
Date: 2012;
Original page

Keywords: SILAC | quantitative proteomics | robust statistics | permutation test | Gaussian mixture model

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) along with other relative quantitation methods in proteomics have become important tools in the analysis of cellular and subcelluar functions. Although numerous experimental applications of SILAC have been developed, there is no consensus on the use of statistical procedures to analyze the resulting experimental data. SILAC experiments output relative abundance ratios for proteins to quantify differences in cell populations. These ratios have traditionally been analyzed with fold-change methods and hypothesis testing procedures under Gaussian distribution assumptions. We find that the normality assumption is invalid and can lead to inaccurate quantitation of the significance of differences between cell populations. As a solution, a permutation based hypothesis test as an alternative for assessing significance is introduced. We develop a distribution-free permutation testing methods for assessing various SILAC experiments. These tests generate p-values which can be easily interpreted and if necessary, the false discovery rate of these p-values can be easily controlled. To compare the permutation test against competing methodology, we used a set of simulations based upon a theoretical model of SILAC ratio data. Through the simulation studies, we find that the permutation test is generally superior to the competing hypothesis tests across the range of simulation scenarios. We also find that the permutation test is typically more powerful and accurate than the competing methods at the five percent level of significance and averaged over the spectrum of significance levels. Because of the broad superiority of the permutation test and the ease of implementation, we propose the use of the permutation test as a standard measure of protein significance in SILAC experiments.
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