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Mapping quantitative trait loci (QTLs) for binary traits in backcross and F2 populations was investigated using stochastic stimulation. Data were analysed using either linear regression or a generalized linear model. Parameters which were varied in the simulations were the population size (200 and 500), heritability in the backcross or F2 population (0·01, 0·05, 0·10), marker spacing (10 and 20 cM) and the incidence of the trait (0·50, 0·25, 0·10). The methods gave very similar results in terms of estimates of the QTL location and QTL effects and power of QTL detection, and it was concluded that in practice treating the zero-one data as continuous and using standard linear regression was efficient.
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