Is There a Bias in Proteome Research?

Advances in technology have enabled us to take a fresh look at data acquired by traditional single experiments and to compare them with genomewide data. The differences can be tremendous, as we show here, in the field of proteomics. We have compared data sets of protein-protein interactions in Saccharomyces cerevisiae that were detected by an identical underlying technical method, the yeast two-hybrid system. We found that the individually identified protein-protein interactions are considerably different from those identified by two genomewide scans. Interacting proteins in the pooled database from single publications are much more closely related to each other with respect to transcription profiles when compared to genomewide data. This difference may have been introduced by two factors: by a selection process in individual publications and by false positives in the whole-genome scans. If we assume that the differences are a result of false positives in the whole-genome data, the scans would contain 47%, 44%, and 91% of false positives for the UETZ, ITO-core, and ITO-full data, respectively. If, however, the true fraction of false positives is considerably lower than estimated here, the data from hypothesis-driven experiments must have been subjected to a serious selection process.