Program in Public Health Genetics, College of Public Health, University of Iowa, Iowa City, Iowa, USA.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S44. doi: 10.1186/1471-2156-6-S1-S44.
The calculation of multipoint likelihoods is computationally challenging, with the exact calculation of multipoint probabilities only possible on small pedigrees with many markers or large pedigrees with few markers. This paper explores the utility of calculating multipoint likelihoods using data on markers flanking a hypothesized position of the trait locus. The calculation of such likelihoods is often feasible, even on large pedigrees with missing data and complex structures. Performance characteristics of the flanking marker procedure are assessed through the calculation of multipoint heterogeneity LOD scores on data simulated for Genetic Analysis Workshop 14 (GAW14). Analysis is restricted to data on the Aipotu population on chromosomes 1, 3, and 4, where chromosomes 1 and 3 are known to contain disease loci. The flanking marker procedure performs well, even when missing data and genotyping errors are introduced.
多点似然计算在计算上具有挑战性,只有在具有许多标记的小系谱或具有少数标记的大系谱上才能精确计算多点概率。本文探讨了使用侧翼标记数据计算多点似然的效用,这些标记假设位于性状基因座的位置。即使在具有缺失数据和复杂结构的大型系谱中,这种似然计算通常也是可行的。通过对遗传分析研讨会 14(GAW14)模拟数据计算多点异质性 LOD 得分来评估侧翼标记程序的性能特征。分析仅限于 Aipotu 人群在染色体 1、3 和 4 上的数据,已知染色体 1 和 3 包含疾病基因座。即使引入缺失数据和基因分型错误,侧翼标记程序也能很好地执行。