[R] How to represent the effect of one covariate on regression results?

[David Winsemius]

There is a user-group for PLINK, easily found by looking at the page you 
cited. This is not the correct place to submit such questions.


https://groups.google.com/g/plink2-users?pli=1


-- 

David.

On 9/14/20 6:29 AM, Ana Marija wrote:
> 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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