Re: question about incorporting genotyping data in disease progression model
Kehua,
Have you tried looking into correlations between the different genotypes? May
be you can collapse them into 2-3 haplotypes if some of those 60 occur
together. I assume these are not all within the same gene.
Quoted reply history
----- Original Message -----
From: "kehua wu" <[email protected]>
To: [email protected]
Sent: Wednesday, August 29, 2012 12:20:39 PM
Subject: [NMusers] question about incorporting genotyping data in disease
progression model
Dear NONMEM users,
I am working on a model in asthma patients and trying to build a model of FEV1,
which is the evaluation of lung function.
I have 500,000 genotyping data. First, I screened the genotyping data by
running GWAS to find out the potential genotyping data, which gave me about 60
genotypes. Then, I tried to add these 60 genotyping data into model to find out
if the progress of FEV1 is related with gene expression.
But the problem is that too many genotypes were related with a significant
change in OFV, which does not sound reasonable to me. I was hoping to find few
(2-3) genotypes are associated with the progress in lung function.
I have tried to include the genotyping data as discrete covariate (if
genotyping =1 then parameter=theta(1); if genotyping =2 then
parameter=theta(2); if genotyping=3 then parameter =theta(3)), and power
function (genotype**(theta)).
Did I do something wrong when including the genotyping data in the model as
covariate?
Thanks a lot in advance!
Kehua