Methods to infer dense genomic information from sparsely genotyped populations

基于DNA多态性或序列的表型预测具有重要的应用，例如在人类医学中预测疾病风险和在植物或动物育种中预测遗传价值。该项目将提高精度，降低关联研究的成本，从而大幅提高此类预测的准确性。 这将允许更有效的遗传改良，特别是在抗病性、减少温室气体排放和产品质量等困难但重要的性状上。 同样的方法可以扩展到改善植物的遗传改良和更好地预测人类疾病的风险。

Prediction of phenotype based on DNA polymorphisms or sequence has important applications such as prediction of disease risk in human medicine and prediction of genetic value in plant or animal breeding. This project will enhance precision and lower the cost of association studies leading to substantial increase in accuracy of such predictions. This will allow more effective genetic improvement, particularly of difficult but important traits such as disease resistance, reduced green-house gas emissions and product quality. The same methods can be extended to improve genetic improvement in plants and better prediction of human disease risk.