单倍型
生物
单倍型估计
连锁不平衡
核苷酸多型性
单核苷酸多态性
遗传关联
系谱图
遗传学
推论
计算生物学
进化生物学
等位基因
基因
基因型
计算机科学
人工智能
作者
Nianjun Liu,Kui Zhang,Hongyu Zhao
标识
DOI:10.1016/s0065-2660(07)00414-2
摘要
Association methods based on linkage disequilibrium (LD) offer a promising approach for detecting genetic variations that are responsible for complex human diseases. Although methods based on individual single nucleotide polymorphisms (SNPs) may lead to significant findings, methods based on haplotypes comprising multiple SNPs on the same inherited chromosome may provide additional power for mapping disease genes and also provide insight on factors influencing the dependency among genetic markers. Such insights may provide information essential for understanding human evolution and also for identifying cis-interactions between two or more causal variants. Because obtaining haplotype information directly from experiments can be cost prohibitive in most studies, especially in large scale studies, haplotype analysis presents many unique challenges. In this chapter, we focus on two main issues: haplotype inference and haplotype-association analysis. We first provide a detailed review of methods for haplotype inference using unrelated individuals as well as related individuals from pedigrees. We then cover a number of statistical methods that employ haplotype information in association analysis. In addition, we discuss the advantages and limitations of different methods.
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