Question

求英语高手人工翻译下！不胜感激 电脑翻译是在是太乱了 。谢谢啦！

1、
Non-parametric linkage analysis. Non-parametric (parameter-free) linkage analysis compares identity-by-descent between affected relatives at a specific location in the genome, as estimated from the marker data, to see whether they are significantly different from Mendelian expectations. Nonrandom assortment of the markers and the trait is expected to occur if markers are linked to a disease locus.
Although non-parametric methods are widely assumed to be more robust than parametric methods, complications arise in the former regarding how statistics should be calculated and assessed when multiple related individuals are affected, particularly when combining evidence from families of different sizes. For example, the affected sib-pair method counts the number of sib-pairs inheriting zero, one or two marker alleles as copies of a specific parental allele and checks whether the resulting numbers are in agreement with the 1:2:1 ratio expected under Mendelian inheritance. However, it has been unclear how to optimally extend this approach to more than two affected siblings. One approach for two-point analysis (involving one marker and disease), made formal by Goring and Terwilliger , is to transform the non-parametric test for a binary trait into a model-based test in which the disease status is recoded in families as a marker-like genotype (a so-called ‘pseudomarker’, see below); linkage of the marker locus is then performed against this pseudomarker. For affected sib-pair designs, this approach is equivalent to analysing the data under a recessive model of inheritance and ,provides near-optimal statistical performance . It is equivalent to the maximum-likelihood binomial method of Abel et al. and the technique can also be extended to ,examine multiple marker loci simultaneously .

若以下回答无法解决问题，邀请你更新回答

Answer 1

1、
1、
Non-parametric linkage analysis. Non-parametric (parameter-free) linkage analysis compares identity-by-descent between affected relatives at a specific location in the genome, as estimated from the marker data, to see whether they are significantly different from Mendelian expectations. Nonrandom assortment of the markers and the trait is expected to occur if markers are linked to a disease locus.
非参数连锁分析。非参数（参数）连锁分析比较身份按血统的影响之间的亲属在一个特定的基因组中的位置，估计从标记的数据，看看是否有明显不同，孟德尔期望。非随机组合的标记和性状预计将发生如果标志有联系的疾病基因。
Although non-parametric methods are widely assumed to be more robust than parametric methods, complications arise in the former regarding how statistics should be calculated and assessed when multiple related individuals are affected, particularly when combining evidence from families of different sizes. For example, the affected sib-pair method counts the number of sib-pairs inheriting zero, one or two marker alleles as copies of a specific parental allele and checks whether the resulting numbers are in agreement with the 1:2:1 ratio expected under Mendelian inheritance. However, it has been unclear how to optimally extend this approach to more than two affected siblings. One approach for two-point analysis (involving one marker and disease), made formal by Goring and Terwilliger , is to transform the non-parametric test for a binary trait into a model-based test in which the disease status is recoded in families as a marker-like genotype (a so-called ‘pseudomarker’, see below); linkage of the marker locus is then performed against this pseudomarker. For affected sib-pair designs, this approach is equivalent to analysing the data under a recessive model of inheritance and ,provides near-optimal statistical performance . It is equivalent to the maximum-likelihood binomial method of Abel et al. and the technique can also be extended to ,examine multiple marker loci simultaneously
虽然非参数方法被广泛认为是更强大的比参数的方法，并发症出现前就如何统计应计算和评估时，多个相关的个人的影响，特别是当结合证据从家庭大小不同的。例如，受影响的同胞对方法计数的同胞对继承零，一个或2个标记等位基因副本的具体父母等位基因和检查是否产生的数字是一致的1:2:1比预期的孟德尔遗传。然而，它一直不清楚如何以最佳方式延长这一办法超过2兄弟姐妹的影响。一个方法的两点分析（涉及一个标志和疾病），正式的戈林和特维莱格，是把非参数检验一个二进制性状为基于模型的测试中，疾病状况记录在家庭作为一个marker-like基因型（所谓的“pseudomarker”，见下文）；联系的标记位点是然后对这pseudomarker。受影响的同胞对设计，这种做法相当于分析数据在隐性遗传模型和统计，提供最优的性能。它是相当于最大似然二项式方法阿贝尔等。和技术还可以扩展，同时检查多个标记位点