Kaplan N L, Weir B S
Statistics and Biomathematics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.
Am J Hum Genet. 1995 Dec;57(6):1486-98.
In the past several years, allelic association has helped map a number of rare genetic diseases in the human genome. A commonly used upper bound on the recombination fraction between the disease gene and an associated marker is known to be biased downward, so there is the possibility that an investigator could be misled. This upper bound is based on a moment equation that can be derived within the context of a Poisson branching process, so its performance can be compared with a recently proposed likelihood bound. We show that the confidence level of the moment upper bound is much lower than expected, while the confidence level of the likelihood bound is in line with expectation. The effects of mutation at either the marker or disease locus on the upper bounds are also investigated. Results indicate that mutation is not an important force for typical mutation rates, unless the recombination fraction between the marker and disease locus is very small or the disease allele is very rare in the general population. Finally, the impact of sample size on the likelihood bound is investigated. The results are illustrated with data on 10 simple genetic diseased in the Finnish population.
在过去几年中，等位基因关联已助力在人类基因组中定位了多种罕见遗传病。已知疾病基因与相关标记之间重组率的常用上限存在向下偏差，因此研究人员有可能被误导。这个上限基于一个矩方程，该方程可在泊松分支过程的背景下推导得出，所以其性能可与最近提出的似然界进行比较。我们表明，矩上限的置信水平远低于预期，而似然界的置信水平符合预期。还研究了标记或疾病位点处的突变对上限的影响。结果表明，对于典型的突变率，突变并非重要因素，除非标记与疾病位点之间的重组率非常小，或者疾病等位基因在一般人群中非常罕见。最后，研究了样本量对似然界的影响。结果通过芬兰人群中10种简单遗传病的数据进行了说明。
