Title:
Pipeline to assess the greatest source of technical variance in quantitative proteomics using metabolic labelling.

Abstract:
The biological variance in protein expression of interest to biologists can only be accessed if the technical variance of the protein quantification method is low compared with the biological variance. Technical variance is dependent on the protocol employed within a quantitative proteomics experiment and accumulated with every additional step. The magnitude of additional variance incurred by each step of a protocol should be determined to enable design of experiments maximally sensitive to differential protein expression. Metabolic labelling techniques for MS based quantitative proteomics enable labelled and unlabelled samples to be combined at the tissue level. It has been widely assumed, although not yet empirically verified, that early combination of samples minimises technical variance in relative quantification. This study presents a pipeline to determine the variance incurred at each stage of a common quantitative proteomics protocol involving metabolic labelling. We apply this pipeline to determine whether early combination of samples in a protocol leads to significant reduction in experimental variance. We also identify which stage within the protocol is associated with maximum variance. This provides a blueprint by which the variance associated with each stage of any protocol can be dissected and utilised to influence optimal experimental design.