Hello,
I was running association analysis using --glm genotypic from:
https://www.cog-genomics.org/plink/2.0/assoc with these covariates:
sex,age,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,TD,array,HBA1C. The
result looks like this:
#CHROM POS ID REF ALT A1 TEST OBS_CT BETA
SE Z_OR_F_STAT P ERRCODE
10 135434303 rs11101905 G A A ADD 11863
-0.110733 0.0986981 -1.12193 0.261891 .
10 135434303 rs11101905 G A A DOMDEV 11863
0.079797 0.111004 0.718868 0.472222 .
10 135434303 rs11101905 G A A sex=Female
11863 -0.120404 0.0536069 -2.24605 0.0247006 .
10 135434303 rs11101905 G A A age 11863
0.00524501 0.00391528 1.33963 0.180367 .
10 135434303 rs11101905 G A A PC1 11863
-0.0191779 0.0166868 -1.14928 0.25044 .
10 135434303 rs11101905 G A A PC2 11863
-0.0269939 0.0173086 -1.55957 0.118863 .
10 135434303 rs11101905 G A A PC3 11863
0.0115207 0.0168076 0.685448 0.493061 .
10 135434303 rs11101905 G A A PC4 11863
9.57832e-05 0.0124607 0.0076868 0.993867 .
10 135434303 rs11101905 G A A PC5 11863
-0.00191047 0.00543937 -0.35123 0.725416 .
10 135434303 rs11101905 G A A PC6 11863
-0.0103309 0.0159879 -0.646172 0.518168 .
10 135434303 rs11101905 G A A PC7 11863
0.00790997 0.0144025 0.549207 0.582863 .
10 135434303 rs11101905 G A A PC8 11863
-0.00205639 0.0142709 -0.144096 0.885424 .
10 135434303 rs11101905 G A A PC9 11863
-0.00873771 0.0057239 -1.52653 0.126878 .
10 135434303 rs11101905 G A A PC10 11863
0.0116197 0.0123826 0.938388 0.348045 .
10 135434303 rs11101905 G A A TD 11863
-0.670026 0.0962216 -6.96337 3.32228e-12 .
10 135434303 rs11101905 G A A array=Biobank
11863 0.160666 0.073631 2.18205 0.0291062 .
10 135434303 rs11101905 G A A HBA1C 11863
0.0265933 0.00168758 15.7583 6.0236e-56 .
10 135434303 rs11101905 G A A GENO_2DF 11863
NA NA 0.726514 0.483613 .
This results is shown just for one ID (rs11101905) there is about 2
million of those in the resulting file.
My question is how do I present/plot the effect of covariate "TD" in
the example it has "P" equal to 3.32228e-12 for all IDs in the
resulting file so that I show how much effect covariate "TD" has on
the analysis. Should I run another regression without covariate "TD"
and than do scatter plot of P values with and without "TD" covariate
or there is a better way to do this from the data I already have?
Thanks
Ana
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