首页> 外文会议>PSB;Pacific symposium on biocomputing; 20090105-09;20090105-09; Kohala Coast, HI(US);Kohala Coast, HI(US) >TREEQA: QUANTITATIVE GENOME WIDE ASSOCIATION MAPPING USING LOCAL PERFECT PHYLOGENY TREES
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TREEQA: QUANTITATIVE GENOME WIDE ASSOCIATION MAPPING USING LOCAL PERFECT PHYLOGENY TREES

机译:TAREEQA:使用局部完善的系统发育树进行定量的基因组广泛关联

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The goal of genome wide association (GWA) mapping in modern genetics is to identify genes or narrow regions in the genome that contribute to genetically complex phenotypes such as morphology or disease. Among the existing methods, tree-based association mapping methods show obvious advantages over single marker-based and haplotype-based methods because they incorporate information about the evolutionary history of the genome into the analysis. However, existing tree-based methods are designed primarily for binary phenotypes derived from case/control studies or fail to scale genome-wide. In this paper, we introduce TreeQA, a quantitative GWA mapping algorithm. TreeQA utilizes local perfect phylogenies constructed in genomic regions exhibiting no evidence of historical recombination. By efficient algorithm design and implementation, TreeQA can efficiently conduct quantitative genom-wide association analysis and is more effective than the previous methods. We conducted extensive experiments on both simulated datasets and mouse inbred lines to demonstrate the efficiency and effectiveness of TreeQA.
机译:现代遗传学中全基因组关联(GWA)映射的目标是识别基因组中的基因或狭窄区域,这些基因或狭窄区域有助于遗传上复杂的表型,例如形态或疾病。在现有方法中,基于树的关联映射方法显示出优于基于单个标记物和基于单倍型的方法的明显优势,因为它们将有关基因组进化史的信息整合到了分析中。但是,现有的基于树的方法主要设计用于案例研究/对照研究得出的二元表型,或者无法在全基因组范围内扩展。在本文中,我们介绍了TreeQA,一种定量的GWA映射算法。 TreeQA利用在基因组区域构建的局部完美系统发育,没有历史重组的迹象。通过有效的算法设计和实现,TreeQA可以有效地进行全基因组定量关联分析,并且比以前的方法更有效。我们对模拟数据集和小鼠自交系进行了广泛的实验,以证明TreeQA的效率和有效性。

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