title: Efficiency of haplotype frequency estimation when nuclear family information is included.
abstract: In genetic studies the haplotype structure of the regarded population is expected to carry important information. Experimental methods to derive haplotypes, however, are expensive and none of them has yet become standard methodology. On the other hand, maximum likelihood haplotype estimation from unphased individual genotypes may incur inaccuracies. We therefore investigated the relative efficiency of haplotype frequency estimation when nuclear family information is included compared to estimation from experimentally derived haplotypes. Efficiency was measured in terms of variance ratios of the estimates. The variances were derived from the binomial distribution for experimentally derived haplotypes, and from the Fisher information matrix corresponding to the general likelihood function of the haplotype frequency parameters, including family information. We subsequently compared these variance ratios to the variance ratios for the case of estimation from individual genotypes. We found that the information gained from a single child compensates missing phase information to a high degree, resulting in estimates almost as reliable as those derived from observed haplotypes. Thus, if children have already been genotyped for other reasons, it is highly recommendable to include them into the estimation. If child information is not already present, it depends on the number of loci and the haplotype diversity if it is useful to genotype a single child just to reduce phase ambiguity. In general, if the number of loci is less than or equal to three or if the number of haplotypes with a frequency >5% is less than or equal to four, haplotype estimation from individuals is quite good already and the improvement gained from a single child can not compensate the genotyping effort for it. On the other hand, under scenarios with many loci and high haplotype diversity, haplotype frequency estimation from trios can be more efficient than haplotype frequency estimation from individuals also on a per genotype base.
authors.affiliation: Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany. becker@imsdd.meb.uni-bonn.de
authors.forename: Tim
authors.initials: T
authors.lastname: Becker
authors.forename: Michael
authors.initials: M
authors.lastname: Knapp
mesh_terms: D003627:Data Interpretation, Statistical; D005787:Gene Frequency; D006239:Haplotypes; D006801:Humans; D016013:Likelihood Functions; D009679:Nuclear Family; D020641:Polymorphism, Single Nucleotide