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HaploBlocker: Creation of Subgroup-Specific Haplotype Blocks and Libraries

机译:HaploBlocker:创建特定于子组的单倍型模块和库

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摘要

The concept of haplotype blocks has been shown to be useful in genetics. Fields of application range from the detection of regions under positive selection to statistical methods that make use of dimension reduction. We propose a novel approach (“HaploBlocker”) for defining and inferring haplotype blocks that focuses on linkage instead of the commonly used population-wide measures of linkage disequilibrium. We define a haplotype block as a sequence of genetic markers that has a predefined minimum frequency in the population, and only haplotypes with a similar sequence of markers are considered to carry that block, effectively screening a dataset for group-wise identity-by-descent. From these haplotype blocks, we construct a haplotype library that represents a large proportion of genetic variability with a limited number of blocks. Our method is implemented in the associated R-package HaploBlocker, and provides flexibility not only to optimize the structure of the obtained haplotype library for subsequent analyses, but also to handle datasets of different marker density and genetic diversity. By using haplotype blocks instead of single nucleotide polymorphisms (SNPs), local epistatic interactions can be naturally modeled, and the reduced number of parameters enables a wide variety of new methods for further genomic analyses such as genomic prediction and the detection of selection signatures. We illustrate our methodology with a dataset comprising 501 doubled haploid lines in a European maize landrace genotyped at 501,124 SNPs. With the suggested approach, we identified 2991 haplotype blocks with an average length of 2685 SNPs that together represent 94% of the dataset.
机译:单倍型模块的概念已被证明在遗传学中是有用的。应用范围从正选择下的区域检测到利用降维的统计方法。我们提出了一种新的方法(“ HaploBlocker”),用于定义和推断单元型模块,该模块侧重于连锁而不是通常在整个人群中使用的连锁不平衡度量。我们将单倍型区块定义为在人群中具有预定最低频率的遗传标记序列,只有具有相似标记序列的单倍型才被认为携带该区块,从而有效地筛选了一个数据集以用于逐族身份。从这些单倍型区块,我们构建了一个单倍型文库,代表了有限数量的区块的大部分遗传变异。我们的方法在相关的R包HaploBlocker中实现,不仅为后续分析提供优化的单倍型文库结构的灵活性,而且还可以处理不同标记密度和遗传多样性的数据集。通过使用单倍型模块代替单核苷酸多态性(SNP),可以自然地建模局部上位相互作用,并且减少的参数数量为实现进一步的基因组分析提供了多种新方法,例如基因组预测和选择标记检测。我们用一个包含501124个SNP基因型的欧洲玉米地方品种的501个双单倍体系的数据集说明了我们的方法。通过建议的方法,我们确定了2991个单倍型模块,平均长度为2685个SNP,合计占数据集的94%。

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