An experimentally-derived measure of inter-replicate variation in reference samples: the same-same permutation methodology

Abstract

The multiple testing problem is a well-known statistical stumbling block in high-25 throughput data analysis, where large scale repetition of statistical methods introduces 26 unwanted noise into the results. While approaches exist to overcome the multiple testing 27 problem, these methods focus on theoretical statistical clarification rather than incorporating 28 experimentally-derived measures to ensure appropriately tailored analysis parameters. Here, 29 we introduce a method for estimating inter-replicate variability in reference samples for a 30 quantitative proteomics experiment using permutation analysis. This can function as a 31 modulator to multiple testing corrections such as the Benjamini-Hochberg ordered Q value 32 test.