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39AjourneywithstatisticalgeneticsElizabeth A. ThompsonDepartment of StatisticsUniversity of Washington, Seattle, WAWith the work of R.A. Fisher and Sewall Wright, the early years of the developmentof methods for analysis of genetic data were closely paralleled bythe broader development of methods for statistical inference. In many ways,the parallel over the last 40 years is no less striking, with genetic and genomicdata providing an impetus for development of broad new areas of statisticalmethodology. While molecular and computational technologies have changedout of all recognition over the last 40 years, the basic questions remain thesame: Where are the genes? What do they do? How do they do it? Thesequestions continue to provide new challenges for statistical science.39.1 Introduction“Plus ça change, plus c’est la même chose.”–AlphonseKarr(1849)No doubt when things work out well, past events seem opportune, butIneverceasetomarvelhowincrediblyluckyIwastoenterthefieldofstatisticalgenetics in 1970. Two foundational books on the theory (Crow andKimura, 1970) and application (Cavalli-Sforza and Bodmer, 1971) of populationgenetics were newly published. Together with the new edition of Stern(1973), these were the bibles of my early graduate-student years. While theavailable data seem primitive by today’s standards, the extensive updates in1976 of the earlier work of Mourant (1954) and colleagues provided a widerview of the genetic variation among human populations than had been previouslyavailable. Computing power for academic research was also fast expanding,with the new IBM 370 series in 1970, and virtual memory capabilitiessoon after.451