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Abstract
Improvements in speed and mass accuracy of mass spectrometers revolutionized proteomics, with high-throughput proteomics enabling the profiling of complete proteomes and thousands of posttranslational modification sites. The limits of high-throughput proteomics are constantly pushed to new frontiers, and mass spectrometry–based proteomics may eventually permit the analysis of protein expression profiles in less than a day. Increased data acquisition speed has led to a dramatic increase in the total number of tandem mass spectrometry (MS/MS) spectra, such that millions of MS/MS spectra are now acquired in a given set of analyses. Many of these spectra are insufficiently validated; instead, statistical tools are commonly used to estimate false-positive or false-discovery rates for these data sets. Many laboratories may not realize the costs associated with using these widely available, but minimally validated, data sets. The costs associated with use of these data can include missed opportunities for biological insight, the pollution of databases with increasing numbers of false-positive identifications, and time spent by biologists investigating false leads, resulting in a lack of faith in proteomics data. Improved strategies for data validation need to be implemented, along with a change in the culture of high-throughput proteomics, linking proteomics closer to biology.
