Complex trait analyses based on genome-wide approaches

该项目旨在开发全基因组方法，通过利用复杂性状的动态遗传结构(即当改变有效种群规模和遗传背景时遗传特征和效应的变化)的信息来提高估计和预测能力。该项目旨在通过结合来自近亲、种群样本或不同种群(如多种族或多品种)的数据，提供先进的统计模型、有效的算法和设计。预期的结果是更好地理解复杂特征的动态结构，并开发出在基因组分析中具有更高威力、精确度和准确性的方法。

This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.