Genetic dissection of even simple Mendelian traits has been sufficiently challenging. Complex traits are proving to be much more challenging and frustrating than previously thought. The concepts, methods, and strategies discussed in this volume emphasize the critical importance of study design, appropriate methods of analysis, including relatively newer and emerging methods, and issues relating to the interpretation of results from genome scans; some thoughts on the future the new millennium holds are offered, as well. This chapter overviews the key steps involved in the study of complex traits, which are discussed in detail in subsequent chapters. It is suggested that a combination of lumping and splitting strategies is more appropriate for the analysis of complex traits, and large-scale collaborations should make this possible. For example, by pooling data and/or results from multiple studies on a given disease/trait, one may attain a sample size large enough to permit the division of the data into multiple relatively more homogeneous subgroups. The sample size of the subgroups may still be sufficiently large sample, but the genetic dissection within each subgroup should be much less daunting. The expectation is that analyses within subgroups will enhance gene finding, especially when any interacting determinants are taken into account at the time of dividing the data into subgroups. Perhaps the methods are not yet optimum, but the future holds much promise. In the meantime, the cutting-edge methods discussed in this volume by leading experts should help. There is an increasing healthy tendency for investigators to collaborate by pooling materials and results across studies, with the goal of increasing the sample size and thus the power. We believe that such efforts are essential for the genetic dissection of complex traits and should contribute to greater success, especially if there is a real commitment to meaningful collaboration. After all, for most complex traits, the question is not whether there are genes, only when and how they might be found.