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    • 6. 发明申请
    • EFFICIENT TESTS OF ASSOCIATION FOR QUANTITATIVE TRAITS AND AFFECTED-UNAFFECTED STUDIES USING POOLED DNA
    • 使用碘化DNA进行定量检测和有针对性的研究的有效测试
    • WO0229110A2
    • 2002-04-11
    • PCT/US0131373
    • 2001-10-09
    • CURAGEN CORPGEMINI GENOMICS LTDBADER JOEL SBANSAL ARUNASHAM PAK
    • BADER JOEL SBANSAL ARUNASHAM PAK
    • A01H1/00C12Q1/68G06F19/18G06F19/22G06F19/00
    • G06F19/18G06F19/22
    • Risk assessment and diagnosis of a complex disorder often requires measuring an underlying quantitative phenotype. Association studies in unrelated populations can implicate genetic factors contributing to disease risk, and experiments using pooled DNA provide a less costly but necessarily less powerful alternative to methods based on individual genotyping. Although the sample sites required for pooling and individual genotyping studies have been compared in certain instances, general results have not been reported in the context of association studies, nor have there been clear comparisons of pooling based on quantitative and qualitative (affected/unaffected) phenotypes. Here we use exact numerical calculations and analytical approximations to examine the sample size requirements of association tests for quantitative traits and affected-unaffected studies using pooled DNA. We show, in analogy with selection experiments, that the optimal design for virtually any quantitative phenotype is to pool the top and bottom 27 % of individuals, regardless of marker frequency or inheritance mode; this design requires a population only 24 % larger than that required for individual genotyping. Furthermore, this design is approximately four times more efficient than typical affected-unaffected studies of DNA pooled from individuals classified as affected or unaffected.
    • 复杂疾病的风险评估和诊断通常需要测量潜在的定量表型。 不相关人群的关联研究可能涉及导致疾病风险的遗传因素,使用合并DNA的实验提供了基于个体基因分型的方法成本较低但必然较不强大的替代方法。 虽然在某些情况下比较了汇集和个体基因分型研究所需的样本地点,但在关联研究的背景下还没有报告一般结果,也没有基于定量和定性(受影响/未受影响)表型的汇总的明确比较 。 在这里,我们使用精确的数值计算和分析近似来检查使用合并的DNA的数量性状和受影响的未受影响的研究的关联检验的样本量要求。 我们类似于选择实验显示,几乎任何定量表型的最佳设计都是汇集个人的顶部和底部27%,而不管标记频率或遗传模式如何; 这种设计需要的人口比单个基因分型所需的人口大24%。 此外,这种设计比从属于受影响或未受影响的个体的DNA的典型受影响的未受影响的研究中大大提高了四倍。
    • 8. 发明申请
    • DNA POOLING METHODS FOR QUANTITATIVE TRAITS USING UNRELATED POPULATIONS OR SIB PAIRS
    • 使用不相关的人口或SIB对的定量旅行的DNA填充方法
    • WO0216643A8
    • 2003-04-10
    • PCT/US0125924
    • 2001-08-20
    • CURAGEN CORPBADER JOEL SBANSAL ARUNASHAM PAK
    • BADER JOEL SBANSAL ARUNASHAM PAK
    • C12Q1/68G01N33/48G01N33/50G06F19/18G06F19/24
    • C12Q1/6883C12Q2600/156G06F19/18G06F19/24
    • Identifying the genetic determinants for disease and disease prediposition remains one of the outstanding goals of the human genome project. When large patient populations are available, genetic approaches using single nucleotide polymorphism markers have the potential to identify relevant genes directly. While indivieual genotyping is the most powerful method for establishing association, determining allele frequencies in DNA pooled on the basis of phenotypic value can also reveal association at much-reduced cost. Here we analyze pooling methods to establish association between a genetic polymorphism and a quantitative phenotype. Exact results are provided for the statistical power for a number of pooling designs where the phenotype is described by a variance components model and the fraction of the population pooled is optimized to minimize the population requirements. For low to moderate sibling phenotypic correlation, unrelated population requirements. For low to moderate sibling phenotypic correlation, unrelated populations are more powerful than sib pair populations with an equal number of individuals, for sibling phenotypic correlations above 75 %, however, designs selecting the sib pairs with the greatest phenotype difference become more powerful. For sibling phenotype correlations below 75 %, pooling extreme unrelated individuals is the most powerful design for sib pair populations. The optimal pooling fractions for each design are constant over a wide range of parameters. These results for quantitative phenotypes differ from those reported for qualitative phenotypes, for which unrelated populations are more powerful than sib pairs and concordant designs are more powerful than discordant, and have immediate relevance to ongoing association studies and anticipated whole-genome scans.
    • 识别疾病和疾病倾向的遗传决定因素仍然是人类基因组计划的突出目标之一。 当大量患者群体可用时,使用单核苷酸多态性标记的遗传方法有可能直接鉴定相关基因。 虽然独立的基因分型是建立关联的最强大的方法,但确定基于表型价值的DNA中等位基因频率的确定也可以显着降低成本。 在这里我们分析汇集方法建立遗传多态性与定量表型之间的关联。 提供了许多汇总设计的统计功能的精确结果,其中表型由方差分量模型描述,并且汇总的人口的分数被优化以最小化人口需求。 对于低至中等同胞表型相关性,无关人口要求。 对于低至中等同胞表型相关性,不相关群体比具有相等数量个体的同胞对群体更强大,对于同位素表型相关性高于75%,然而,选择具有最大表型差异的同胞对的设计变得更加强大。 对于低于75%的同胞表型相关性,汇集极端不相关的个​​体是同胞对群体最强大的设计。 每个设计的最佳合并分数在广泛的参数范围内是恒定的。 定量表型的这些结果与针对定性表型报道的结果不同,对于这些结果,不相关的人群比同胞对更强大,一致的设计比不一致更强大,并且与正在进行的关联研究和预期的全基因组扫描具有直接关联。
    • 9. 发明申请
    • DNA POOLING METHODS FOR QUANTITATIVE TRAITS USING UNRELATED POPULATIONS OR SIB PAIRS
    • 使用不相关的人口或SIB对的定量旅行的DNA填充方法
    • WO0216643A3
    • 2004-02-26
    • PCT/US0125924
    • 2001-08-20
    • CURAGEN CORPBADER JOEL SBANSAL ARUNASHAM PAK
    • BADER JOEL SBANSAL ARUNASHAM PAK
    • C12Q1/68G01N33/48G01N33/50G06F19/18G06F19/24G06F19/00
    • C12Q1/6883C12Q2600/156G06F19/18G06F19/24
    • Identifying the genetic determinants for disease and disease prediposition remains one of the outstanding goals of the human genome project. When large patient populations are available, genetic approaches using single nucleotide polymorphism markers have the potential to identify relevant genes directly. While indivieual genotyping is the most powerful method for establishing association, determining allele frequencies in DNA pooled on the basis of phenotypic value can also reveal association at much-reduced cost. Here we analyze pooling methods to establish association between a genetic polymorphism and a quantitative phenotype. Exact results are provided for the statistical power for a number of pooling designs where the phenotype is described by a variance components model and the fraction of the population pooled is optimized to minimize the population requirements. For low to moderate sibling phenotypic correlation, unrelated population requirements. For low to moderate sibling phenotypic correlation, unrelated populations are more powerful than sib pair populations with an equal number of individuals, for sibling phenotypic correlations above 75 %, however, designs selecting the sib pairs with the greatest phenotype difference become more powerful. For sibling phenotype correlations below 75 %, pooling extreme unrelated individuals is the most powerful design for sib pair populations. The optimal pooling fractions for each design are constant over a wide range of parameters. These results for quantitative phenotypes differ from those reported for qualitative phenotypes, for which unrelated populations are more powerful than sib pairs and concordant designs are more powerful than discordant, and have immediate relevance to ongoing association studies and anticipated whole-genome scans.
    • 识别疾病和疾病倾向的遗传决定因素仍然是人类基因组计划的突出目标之一。 当大量患者群体可用时,使用单核苷酸多态性标记的遗传方法有可能直接鉴定相关基因。 虽然独立的基因分型是建立关联的最强大的方法,但确定基于表型价值的DNA中等位基因频率的确定也可以显着降低成本。 在这里我们分析汇集方法建立遗传多态性与定量表型之间的关联。 提供了许多汇总设计的统计功能的精确结果,其中表型由方差分量模型描述,并且汇总的人口的分数被优化以最小化人口需求。 对于低至中等同胞表型相关性,无关人口要求。 对于低至中等同胞表型相关性,不相关群体比具有相等数量个体的同胞对群体更强大,对于同位素表型相关性高于75%,然而,选择具有最大表型差异的同胞对的设计变得更加强大。 对于低于75%的同胞表型相关性,汇集极端不相关的个​​体是同胞对群体最强大的设计。 每个设计的最佳合并分数在广泛的参数范围内是恒定的。 定量表型的这些结果与针对定性表型报道的结果不同,对于这些结果,不相关的人群比同胞对更强大,一致的设计比不一致更强大,并且与正在进行的关联研究和预期的全基因组扫描具有直接关联。