Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp. Keywords: FDR / Multiple testing corrections / Shot gun proteomics ViewpointMultiple testing corrections come in many "flavors." They are employed to limit the number of false positives occurring by chance when an analysis is repeated many times and thus to reduce the FDR at the analysis level. In proteomics they were initially borrowed from microarray research and other high throughput areas, where they quickly became the norm. The informative review by Diz [1] shows that multiple testing corrections were seldom used in quantitative proteomics until relatively recently, and recommends a sensible multimethod approach. Here, we suggest that one reason for the slower uptake of such methods in proteomics experiments, despite their ease of use and theoretical appeal, is that they remain a useful but blunt tool that is less effective in discovery proteomics than in, for example, the microarray environment. In this paper, we describe five key factors that combine to make multiple testing corrections less effective in proteomics: medium problem scale; lower effect size due to possible compression; lower analysis power due to high cost; percentage of data showing an effect; and data distribution quirks. We then discuss some simple alternatives that can help reduce, or at least understand the FDR in this medium scale, low power situation.

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. Data Independent Acquisition (DIA) 1 mass spectrometry workflows are gaining increasing use for proteomic analysis of model systems (1-8). The first integrated DIA and quantitative analysis protocol, termed SWATH (2) was shown to offer accurate, reproducible, and robust proteomic quantification (9 -14). DIA offers advantages over conventional IDA methods (15) by overcoming the stochastic, intensity-based selection of peptide precursors-a problem which typically leads to inconsistent peptide detection and quantitation between replicate runs. By overcoming this problem, DIA is highly suited for large-scale comparative analyses as gaps in data points between samples are mostly eliminated. These digital, extensive proteome maps can be repeatedly mined for quantitative data by extracting ion chromatograms of defined peptides postacquisition, and yields fewer quantitative missing (NA) values than IDA. An important concept in DIA analysis is use of a LC-retention time referenced spectral ion assay library to enable peptide identification from DIA generated multiplexed MS/MS spectra (10,13,16). The depth and quality of this spectral reference library directly correlates with experimental outcome, therefore we consider it is essential to explore and understand this variable in detail.The reference assay library should contain all the prior knowle...

BackgroundCabernet Sauvignon grapevines were exposed to a progressive, increasing water defict over 16 days. Shoot elongation and photosynthesis were measured for physiological responses to water deficit. The effect of water deficit over time on the abundance of individual proteins in growing shoot tips (including four immature leaves) was analyzed using nanoflow liquid chromatography - tandem mass spectrometry (nanoLC-MS/MS).ResultsWater deficit progressively decreased shoot elongation, stomatal conductance and photosynthesis after Day 4; 2277 proteins were identified by shotgun proteomics with an average CV of 9% for the protein abundance of all proteins. There were 472 out of 942 (50%) proteins found in all samples that were significantly affected by water deficit. The 472 proteins were clustered into four groups: increased and decreased abundance of early- and late-responding protein profiles. Vines sensed the water deficit early, appearing to acclimate to stress, because the abundance of many proteins changed before decreases in shoot elongation, stomatal conductance and photosynthesis. Predominant functional categories of the early-responding proteins included photosynthesis, glycolysis, translation, antioxidant defense and growth-related categories (steroid metabolism and water transport), whereas additional proteins for late-responding proteins were largely involved with transport, photorespiration, antioxidants, amino acid and carbohydrate metabolism.ConclusionsProteomic responses to water deficit were dynamic with early, significant changes in abundance of proteins involved in translation, energy, antioxidant defense and steroid metabolism. The abundance of these proteins changed prior to any detectable decreases in shoot elongation, stomatal conductance or photosynthesis. Many of these early-responding proteins are known to be regulated by post-transcriptional modifications such as phosphorylation. The proteomics analysis indicates massive and substantial changes in plant metabolism that appear to funnel carbon and energy into antioxidant defenses in the very early stages of plant response to water deficit before any significant injury.