首页> 外文会议>Eighth Pacific Symposium on Biocomputing (PSB), Jan 3-7, 2003, Kauai, Hawaii >ON THE POWER TO DETECT SNP/PHENOTYPE ASSOCIATION IN CANDIDATE QUANTITATIVE TRAIT LOCI GENOMIC REGIONS: A SIMULATION STUDY
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ON THE POWER TO DETECT SNP/PHENOTYPE ASSOCIATION IN CANDIDATE QUANTITATIVE TRAIT LOCI GENOMIC REGIONS: A SIMULATION STUDY

机译:定量性状特异基因组区域检测SNP /表型关联的能力的模拟研究

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We use coalescent methods to investigate the ability of linked neutral 'markers" to reveal in simulated population samples the presence of one or more single nucleotide polymorphisms that is contributing to a trait having a complex genetic basis (QTN: quantitative trait nucleotide). Realistic mutation and recombination rates in our simulations allow us to generate SNP data appropriate for analyzing human variation across short chromosomal intervals corresponding to approximately 100 kilobases. We investigate the performance of both single marker and multiple-marker (haplotype) data for several ad hoc procedures. Our results with single SNP markers indicate that (1) the density of SNP markers need not be much higher than 10% in order to achieve near-maximal detection of a QTN; (2) a higher density of markers does not improve much on the ability to localize a QTN within an interval unless the recombination rate is high. Haplotype-based tests were investigated for the case in which more than one QTN is present in the studied interval. Larger sample sizes improve both the probability of detecting the haplotype with the largest number of QTNs, as well as the ability to infer correct haplotypes from genotypic data. Testing a series of short haplotypes across a longer interval can also be beneficial. The rate of false positives (i.e., when the most significant haplotype does not contain the greatest number of QTNs in the sample) can be very high when the contribution of individual QTNs to a trait is small. The elimination of low-frequency haplotypes does not substantially reduce the probability of detecting the haplotype with the largest number of QTNs but it can reduce the rate of false positives.
机译:我们使用合并方法来研究链接的中性“标记”在模拟的群体样本中揭示一个或多个单核苷酸多态性的存在的能力,这些多态性有助于具有复杂遗传基础的性状(QTN:定量性状核苷酸)。模拟中的重组率和重组率使我们能够生成适合分析短染色体间隔(对应于大约100千个碱基)中的人类变异的SNP数据,我们研究了几种特定程序的单标记和多标记(单倍型)数据的性能。单个SNP标记的结果表明:(1)SNP标记的密度不需要达到10%即可达到QTN的最大检测;(2)更高的标记密度并不能大大提高检测能力除非重组率很高,否则将在一定间隔内定位QTN。在研究的间隔中存在一个QTN。较大的样本量会提高检测到具有最大数量QTN的单倍型的可能性,以及从基因型数据推断正确单倍型的能力。在较长的间隔内测试一系列短单倍型也可能是有益的。当单个QTN对性状的贡献较小时,假阳性率(即,当最重要的单倍型不包含最大数量的QTN时)可能很高。消除低频单倍型不会显着降低检测到具有最大数量QTN的单倍型的可能性,但可以降低误报率。

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