Combining Protein Ratio <i>p</i>‑Values as a Pragmatic Approach to the Analysis
of Multirun iTRAQ Experiments
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Abstract
iTRAQ
labeling of peptides is widely used for quantitative comparison of
biological samples using mass spectrometry. However, iTRAQ determined
protein ratios have varying credibility depending on the number and
quality of the peptide ratios used to generate them, and accounting
for this becomes problematic particularly in the multirun scenario
needed for larger scale biological studies. One approach to this problem
relies on the use of sophisticated statistical global models using <i>peptide</i> ratios rather than working directly with the <i>protein</i> ratios, but these yield complex models whose solution
relies on computational approaches such as stage-wise regression,
which are nontrivial to run and verify. Here we evaluate an alternative
pragmatic approach to finding differentially expressed proteins based
on combining protein ratio <i>p</i>-values across experiments
in a fashion similar to running a meta-analysis across different iTRAQ
runs. Our approach uses the well-established Stouffer’s Z-transform
for combining <i>p</i>-values, alongside a ratio trend consistency
measure, which we introduce. We evaluate this method with data from
two iTRAQ experiments using plant and animal models. We show that
in the specific context of iTRAQ data analysis this method has advantages
of simplicity, high tolerance of run variability, low false discovery
rate, and emphasis on proteins identified with high confidence