**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 and Hochberg 1995

: 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.