We present a multipoint algorithm to map quantitative trait loci (QTLs) using families from outbred populations with a variable number of sibs. The algorithm uses information from all markers on a chromosome simultaneously to extract information of QTL segregation. A previous multipoint method (Kruglyak & Lander (1995) American Journal of Human Genetics 57, 439–454) extracts information using a hidden Markov model. However, this method is restricted to small families (<10 sibs). We present an approximate hidden Markov model approach that can handle large sibships while retaining similar efficiency to the previous method. Computer simulations support the notion that data sampled from a small number of large families provide more power than data obtained from a large number of small families, under the constraint that the total number of individuals for the two schemes is the same. This is further reflected in simulations with variable family sizes, where variance in family size improves the statistical power of QTL detection relative to a constant size control.
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