Copy-number variation (CNV) is the most prevalent type of structural variation in the human genome, and contributes significantly to genetic heterogeneity. It has already been recognized that some CNVs can contribute to human phenotype, including rare genomic disorders and Mendelian diseases. Other CNVs are now amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be more readily determined. Population studies and reference databases for control and disease-associated samples are required to provide an information resource about CNV frequencies and their relative contribution to phenotypic outcomes. The relatively high cost of screening individual samples has tended to limit the number of controls assayed, and use of the data has often been hampered by the variety of technology platforms and analysis techniques. As a result, there is still a paucity of data on population frequency and distribution of CNVs, particularly for those that are rare. Here, we provide an example of how to discover new CNVs from existing genotype data from large-scale genetic epidemiological studies. We also discuss the need to expand surveys of CNV in different population-based cohorts and to apply the information to studies of human variation and disease.