How to do statistical analysis of genetic association studies?
Statistical Analysis of Case–Control Study The genotypes of a single, biallelic SNP on a set of cases and controls can be summarized in a 2 × 3 contingency table of the genotype counts for each group, as shown in Figure 1.
When to use genome wide association analysis ( GWA )?
In the present manuscript, we focus on the analysis of data arising from population-based GWA studies of unrelated individuals where primary interest resides in identifying associations between SNPs and a single binary, for example, case or control status or quantitative phenotype.
How are SNPs coded in genome wide association analysis?
Here, each SNP is bi-allelic (i.e., only two nucleotides are observed at any given SNP across study participants) and coded as a pair of nucleotides (A, C, T, or G). Notably, the ordering in the pair is non-informative in the sense that the first alleles listed for each of the two SNPs are not necessarily on the same chromosome.
When does population stratification occur in genetic studies?
Population stratification arises in case–control studies when the two study groups are poorly matched for genetic ancestry. Confounding then occurs between disease state (case, control) and genetic ancestry, with a subsequent increase in false-positive associations.
Which is a valid test for genetic association?
Both control sets form a valid test for association, and they will have similar power for a rare disease.
How are controls collected in a genetic study?
Two standard methods are used for collecting controls: the use of either a series of individuals who have been screened as negative for presence of the disease or of controls randomly ascertained from the population, whose disease status is unknown.
Which is the best method for genetic analysis?
Other analysis methods that correspond to the underlying genetic models we expect to be acting in complex diseases may be preferred.