I am doing gwas analyses using twins data. after quality control in plink, over 6 millions variants and 2400 individuals are left for conducting association analyses. i didvided the variants into 22 subsets based on chromosomes and run parallel analyses for each variant in each subset in R/4.2.0. i used lme4
package, C1 to C10 are principal components. my model is as follows:
lmm=lmer(phenotype~variant_i+C1+C2+C3+C4+C5+C6+C7+C8+C9+C10+(1|FamilyID)+(1|zygosity),data=chr1
But there is no p value for variant_i from the summary(lmm). how can I get the p values and identify the genome-wide significant variants for the phenotype?
