Linkage disequilibrium(LD) can be applied for mapping the actual genes responsible for variation of economically important traits through association mapping.The feasibility and efficacy of association studies are str...Linkage disequilibrium(LD) can be applied for mapping the actual genes responsible for variation of economically important traits through association mapping.The feasibility and efficacy of association studies are strongly dependent on the extent of LD which determines the number and density of markers in the studied population,as well as the experimental design for an association analysis.In this study,we first characterized the extent of LD in a wild population and a cultured mass-selected line of Pacific oyster(Crassostrea gigas).A total of 88 wild and 96 cultured individuals were selected to assess the level of genome-wide LD with 53 microsatellites,respectively.For syntenic marker pairs,no significant association was observed in the wild population;however,three significant associations occurred in the cultured population,and the significant LD extended up to 12.7 c M,indicating that strong artificial selection is a key force for substantial increase of genome-wide LD in cultured population.The difference of LD between wild and cultured populations showed that association studies in Pacific oyster can be achieved with reasonable marker densities at a relatively low cost by choosing an association mapping population.Furthermore,the frequent occurrence of LD between non-syntenic loci and rare alleles encourages the joint application of linkage analysis and LD mapping when mapping genes in oyster.The information on the linkage disequilibrium in the cultured population is useful for future association mapping in oyster.展开更多
We start with a description of the statistical inferential framework and the duality between observed data and the true state of nature that underlies it. We demonstrate here that the usual testing of dueling hypothes...We start with a description of the statistical inferential framework and the duality between observed data and the true state of nature that underlies it. We demonstrate here that the usual testing of dueling hypotheses and the acceptance of one and the rejection of the other is a framework which can often be faulty when such inferences are applied to individual subjects. This follows from noting that the statistical inferential framework is predominantly based on conclusions drawn for aggregates and noting that what is true in the aggregate frequently does not hold for individuals, an ecological fallacy. Such a fallacy is usually seen as problematic when each data record represents aggregate statistics for counties or districts and not data for individuals. Here we demonstrate strong ecological fallacies even when using subject data. Inverted simulations, of trials rightly sized to detect meaningful differences, yielding a statistically significant p-value of 0.000001 （1 in a million） and associated with clinically meaningful differences between a hypothetical new therapy and a standard therapy, had a proportion of instances of subjects with standard therapy effect better than new therapy effects close to 30%. A ―winner take all‖ choice between two hypotheses may not be supported by statistically significant differences based on stochastic data. We also argue the incorrectness across many individuals of other summaries such as correlations, density estimates, standard deviations and predictions based on machine learning models. Despite artifacts we support the use of prospective clinical trials and careful unbiased model building as necessary first steps. In health care, high touch personalized care based on patient level data will remain relevant even as we adopt more high tech data-intensive personalized therapeutic strategies based on aggregates.展开更多
We present a mean field study of a propagation-tumover lattice model, which was proposed by Hodges and Crabtree [Proc. Nat. Acad. Sci. 109, 13296 （2012）] for understanding how posttranslational histone marks modulat...We present a mean field study of a propagation-tumover lattice model, which was proposed by Hodges and Crabtree [Proc. Nat. Acad. Sci. 109, 13296 （2012）] for understanding how posttranslational histone marks modulate gene expression in mammalian ceils. The kinetics of the lattice model consists of nucleation, propagation and turnover mechanisms, and exhibits second-order phase transition for the histone marking domain. We showed rigorously that the dynamics essentially depends on a non-dimensional parameter k = k＋/k-, the ratio between the propagation and turnover rates, which has been observed in the simulations. We then studied the lowest order mean field approximation, and observed the phase transition with an analytically obtained critical parameter. The boundary layer analysis was utilized to investigate the structure of the decay profile of the mark density. We also studied the higher order mean field approximation to achieve sharper estimate of the critical transition parameter and more detailed features. The comparison between the simulation and theoretical results shows the validity of our theory.展开更多
基金supported by the Shandong Seed Project and the National Natural Science Foundation of China (31372524)
文摘Linkage disequilibrium(LD) can be applied for mapping the actual genes responsible for variation of economically important traits through association mapping.The feasibility and efficacy of association studies are strongly dependent on the extent of LD which determines the number and density of markers in the studied population,as well as the experimental design for an association analysis.In this study,we first characterized the extent of LD in a wild population and a cultured mass-selected line of Pacific oyster(Crassostrea gigas).A total of 88 wild and 96 cultured individuals were selected to assess the level of genome-wide LD with 53 microsatellites,respectively.For syntenic marker pairs,no significant association was observed in the wild population;however,three significant associations occurred in the cultured population,and the significant LD extended up to 12.7 c M,indicating that strong artificial selection is a key force for substantial increase of genome-wide LD in cultured population.The difference of LD between wild and cultured populations showed that association studies in Pacific oyster can be achieved with reasonable marker densities at a relatively low cost by choosing an association mapping population.Furthermore,the frequent occurrence of LD between non-syntenic loci and rare alleles encourages the joint application of linkage analysis and LD mapping when mapping genes in oyster.The information on the linkage disequilibrium in the cultured population is useful for future association mapping in oyster.
文摘We start with a description of the statistical inferential framework and the duality between observed data and the true state of nature that underlies it. We demonstrate here that the usual testing of dueling hypotheses and the acceptance of one and the rejection of the other is a framework which can often be faulty when such inferences are applied to individual subjects. This follows from noting that the statistical inferential framework is predominantly based on conclusions drawn for aggregates and noting that what is true in the aggregate frequently does not hold for individuals, an ecological fallacy. Such a fallacy is usually seen as problematic when each data record represents aggregate statistics for counties or districts and not data for individuals. Here we demonstrate strong ecological fallacies even when using subject data. Inverted simulations, of trials rightly sized to detect meaningful differences, yielding a statistically significant p-value of 0.000001 （1 in a million） and associated with clinically meaningful differences between a hypothetical new therapy and a standard therapy, had a proportion of instances of subjects with standard therapy effect better than new therapy effects close to 30%. A ―winner take all‖ choice between two hypotheses may not be supported by statistically significant differences based on stochastic data. We also argue the incorrectness across many individuals of other summaries such as correlations, density estimates, standard deviations and predictions based on machine learning models. Despite artifacts we support the use of prospective clinical trials and careful unbiased model building as necessary first steps. In health care, high touch personalized care based on patient level data will remain relevant even as we adopt more high tech data-intensive personalized therapeutic strategies based on aggregates.
基金supported by the National Natural Science Foundation of China (Grant Nos. 11174011, 11021463, 11421101, and 91530322)
文摘We present a mean field study of a propagation-tumover lattice model, which was proposed by Hodges and Crabtree [Proc. Nat. Acad. Sci. 109, 13296 （2012）] for understanding how posttranslational histone marks modulate gene expression in mammalian ceils. The kinetics of the lattice model consists of nucleation, propagation and turnover mechanisms, and exhibits second-order phase transition for the histone marking domain. We showed rigorously that the dynamics essentially depends on a non-dimensional parameter k = k＋/k-, the ratio between the propagation and turnover rates, which has been observed in the simulations. We then studied the lowest order mean field approximation, and observed the phase transition with an analytically obtained critical parameter. The boundary layer analysis was utilized to investigate the structure of the decay profile of the mark density. We also studied the higher order mean field approximation to achieve sharper estimate of the critical transition parameter and more detailed features. The comparison between the simulation and theoretical results shows the validity of our theory.
