SNPs screening (Associations between each SNP and outcomes)
This module tests for association between each SNP and each phenotype.
SNP data could be from a .ped file. For each SNP, three models: additive, dominant and recessive will be tested. If the phenotype is a continuous variable, this module will also generate adjusted mean (and standard error) of phenotype for each genotype (AA, AB or BB).
The output table includes following columns:
· SNP name,
· Phenotype name,
· Group (if a stratified variable was specified)
· N0, N1, N2: number of observations used that had genotype=AA, AB, BB respectively
· ß(add), se(add), p(add): regression coefficient, standard error and P-value from additive model
· ß(dom), se(dom), p(dom): regression coefficient, standard error and P-value from dominant model
· ß(rec), se(rec), p(rec): regression coefficient, standard error and P-value from recessive model
· lsmean0, lsmean1, lsmean2: adjusted mean for people with AA, AB, BB genotype respectively
· fdrcut: FDR cut point for P-value from additive model (Benjamini
: sort p values [k=1 to m], start at biggest p value, stop when p <= 0.05*k/m)
This module was used to do an initial screening over a large amount of SNPs. It helps us to quickly identify most significant SNPs.