For a long time, researchers have been facing the challenges of population stratification in genetic association studies. Due to the potential of population stratification to cause false positives and false negatives, if not properly corrected, it may mask true association signals. In the analysis of rare variant associations, this issue can become even more challenging because rare variants are difficult to detect. To address the aforementioned issue, this paper introduces a method, the optimal weighted aggregate (C-TOWA), for assessing the effects of variants in admixed populations and detecting associations between genetic loci and trait values. The method takes into account the weights of variants that are strongly associated with the phenotype, that is, optimally deriving weights based on existing phenotype and genotype data. We assessed the execution of the C-TOWA method through wide-ranging simulation experiments. The simulation results show that C-TOWA can effectively control population stratification effects and is the most powerful in nearly all scenarios.
With the development of genome-wide association analysis and sequencing techniques, lots of rare and common variants associated with complex traits or diseases have been detected. Besides, in recent years, the research based on family data has attracted wide attention, but most of the research only consider the data of unrelated individuals and siblings, and rarely consider the data of distant relatives like grandparent-grandchild pairs, uncle-nephew pairs, cousin pairs, and so on. In this paper, we propose an effective method for generating affected grandparent-grandchild pair data (called GAGP). Based on association analysis, we use a large number of simulation experiments to evaluate the effectiveness and application of the new sampling method. The simulation results show that in all cases, the new method is valid and obtains good test results compared with other methods, which indicates that the method has better performance. The new method is implemented by the software R.
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