Application Of Two - Step Method In Quantitative Trait Correlation Analysis

Genome-wide association studies is a research which uses a lot of samples to verify the association between genes and diseases at the whole genome level. As an important tool to discover the susceptible gene of the complex diseases, Genomewide association studies have successfully helped the researchers to ?nd thousands of SNPs associated with a variety of diseases. Comparing with one-step approaches,two-step approaches can reduce sequencing work and cost signi?cantly. Two-step approaches use the same sample, and choose two di?erent statistics in the two steps.In the ?rst step, we screen a lot of genomic markers and select some remarkable SNPs. Then we test the SNPs which were selected in the ?rst step and determine the SNPs which are associated with the disease. Currently, two-step approaches become one of the most common approaches in the Genome-wide association studies.For family data, the correlation information can be divided into between-family information and within-family information. In the ?rst step, we can use betweenfamily information to screen SNPs; In the second step, we can use within-family information to analyse the correlation for those SNPs which were selected in the?rst step.In this dissertation, we make thorough study of the existing two-step approaches,and propose a new two-step approach. Based on nuclear family data, we use two unrelated statistics to screen and select for those SNPs, then we conduct simulation studies to evaluate the type I error rates and powers of the two-step approach and compar with other methods.