Since the publication of the Saccharomyces cerevisiae genome sequence, much effort has been dedicated to developing high-throughput techniques to generate comprehensive information about the function and dynamics of all genes in this yeast's genome. These techniques have generated data sets that typically contain large amounts of reliable and valuable biological information. Nevertheless, there are also uncertainties that are associated with such large-scale studies, which we discuss in this review. These uncertainties increase with the complexity of the organism under study. On the basis of the results from yeast, we should learn much from human and mouse genomic data sets. However, as with yeast data sets, they might also contain misleading results.