The easiest way would be through a linear regression (you can use R, SAS, even MS Excel). All what you have to do is to code your alleles as 0-1-2 {AA, Aa, aa}, then regress the phenotype over that SNP. Simple like that: The beta coefficient is you effect of an allele substitution.

For dominance, the procedure is the same, but you code you alleles as 0-1-0 {AA, Aa, aa}. You may want to consider fit both additive and dominance effect at the same time. In which case, the regression coefficient of dominance indicate what kind of dominance this locus display (under dominance, over dominance, complete dominance, etc.).

Thank you very much Davide.

The easiest way would be through a linear regression (you can use R, SAS, even MS Excel). All what you have to do is to code your alleles as 0-1-2 {AA, Aa, aa}, then regress the phenotype over that SNP. Simple like that: The beta coefficient is you effect of an allele substitution.

For dominance, the procedure is the same, but you code you alleles as 0-1-0 {AA, Aa, aa}. You may want to consider fit both additive and dominance effect at the same time. In which case, the regression coefficient of dominance indicate what kind of dominance this locus display (under dominance, over dominance, complete dominance, etc.).

Both Plink and GWAS packages in R can do this.

 Thank you very much your suggestions. it was very helpful.

Hi Man.

The PLINK seems like the best way!

Can you use the command:

plink --file mydata --model

(The genotypic test provides a general test of association in the 2-by-3 table of disease-by-genotype. The dominant and recessive models are tests for the minor allele (which is the minor allele can be found in the output of either the --assoc or the --freq commands. That is, if D is the minor allele (and d is the major allele): Allelic: D versus d

Dominant: (DD, Dd) versus dd

Recessive: DD versus (Dd, dd)

Genotypic: DD versus Dd versus dd)

As mentioned above, these tests are generated  a file plink.model

which contains the following fields:

CHR Chromosome number

SNP SNP identifier

TEST Type of test

AFF Genotypes/alleles in cases

UNAFF Genotypes/alleles in controls

CHISQ Chi-squated statistic

DF Degrees of freedom for test

P Asymptotic p-value

@Jingwei Yuan

How we can analyse on R and what type of R coding used?

@Muhammad Kashif Naeem

The 'GenABEL' Package in r can do genome-wide or single SNP association analysis. 

thanks!