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Efficient Inference of Haplotypes From Genotypes on a Large Animal Pedigree

机译:从大型动物谱系的基因型单倍型的有效推断。

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摘要

We present a simple algorithm for reconstruction of haplotypes from a sample of multilocus genotypes. The algorithm is aimed specifically for analysis of very large pedigrees for small chromosomal segments, where recombination frequency within the chromosomal segment can be assumed to be zero. The algorithm was tested both on simulated pedigrees of 155 individuals in a family structure of three generations and on real data of 1149 animals from the Israeli Holstein dairy cattle population, including 406 bulls with genotypes, but no females with genotypes. The rate of haplotype resolution for the simulated data was >91% with a standard deviation of 2%. With 20% missing data, the rate of haplotype resolution was 67.5% with a standard deviation of 1.3%. In both cases all recovered haplotypes were correct. In the real data, allele origin was resolved for 22% of the heterozygous genotypes, even though 70% of the genotypes were missing. Haplotypes were resolved for 36% of the males. Computing time was insignificant for both data sets. Despite the intricacy of large-scale real pedigree genotypes, the proposed algorithm provides a practical rule-based solution for resolving haplotypes for small chromosomal segments in commercial animal populations.
机译:我们提出了一种从多基因座基因型样本中重建单倍型的简单算法。该算法专门针对小染色体片段的超大谱系进行分析,其中染色体片段内的重组频率可以假定为零。对该算法进行了测试,包括三代家庭结构中的155个个体的模拟谱系以及以色列荷斯坦奶牛种群的1149只动物的真实数据,其中包括406名具有基因型的公牛,但没有雌性的基因型。模拟数据的单倍型解析率> 91%,标准差为2%。在缺少20%数据的情况下,单倍型解析率为67.5%,标准偏差为1.3%。在这两种情况下,所有恢复的单倍型都是正确的。在真实数据中,即使缺失了70%的基因型,等位基因的起源也被解析为22%的杂合基因型。 36%的男性单倍型得到解决。对于这两个数据集,计算时间都微不足道。尽管大型真实谱系基因型错综复杂,但该算法为商业动物种群中小染色体片段的单倍型解析提供了一种实用的基于规则的解决方案。

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