A new approach to the problem of multiple comparisons in the genetic dissection of complex traits

Saturated genetic marker maps are being used to map individual genes affect ing quantitative traits. Controlling the "experimentwise" type-I error seve rely lowers power to detect segregating loci. For preliminary genome scans, we propose controlling the "false discovery rate," that is, the expected p roportion of true null hypotheses within the class of rejected null hypothe ses. Examples are given based on a granddaughter design analysis of dairy c attle and simulated backcross populations. By controlling the false discove ry rate, power to detect true effects is not dependent on the number of tes ts performed. If no detectable genes are segregating, controlling the false discovery rate is equivalent to controlling the experimentwise error rate. If quantitative loci are segregating in the population, statistical power is increased as compared to control of the experimentwise type-I error. The difference between the two criteria increases with the increase in the num ber of false null hypotheses. The false discovery rate can be controlled at the same level whether the complete genome or only part of it has been ana lyzed. Additional levels of contrasts, such as multiple traits or pedigrees , can be handled without the necessity of a proportional decrease in the cr itical test probability.