I have an Illumina GWAS data set with ~900 samples and 10 quantitative traits related to Obesity (BMI,weight, waist circumference), Diabetes (PGL), Hypertension (SBP, DBP) and Lipid profiles (TGL,T.Cholestrol, HDL,LDL). I use PLINK for QC and statistical association analysis. QC is performed as per standard protocols. After performing QC I have done LD pruning using PLINK to do PCA using EIGENSTRAT.
Original data set had ~7,00,000 (close to 1 million) SNPs, after doing QC, it turned out to be ~6,00,000 SNPs. Following this, LD pruning reduced SNPs to ~3,00,000. I have done statistical association analysis on two data sets, one with ~6,00,000 SNPs and other with 3,00,000 SNPs (LD pruned set) separately. While doing statistical association analysis (--linear) I have adjusted for Age, Sex and first 10 Principle components.
However, I have some confusion on p-value threshold calculation. I have seen couple of links where they say 0.05 / number of snps would give p-value threshold. But, do I have to consider 12 covariates used in --linear for calculation of p-value threshold? I will be grateful if you can clarify this to me? Thanking you in anticipation.