[GenABEL-dev] faster polygenic

William Astle william.astle at imperial.ac.uk
Wed Mar 2 16:59:13 CET 2011


On 02/03/11 15:15, Yurii Aulchenko wrote:
>> That's interesting, I guess the extra variance inflation is probably due to
>> uncertainty in K which we don't model. I've wondered about extending the
>> method to work with an uncertain K, I'm not sure how feasible statistically
>> or computationally that would be.
> This is very interesting suggestion -- never quite thought of what
> woul the effects of uncertainty of K be onto test statistics. My
> feeling is that uncertainty in K is likely to translate into
> uncertainty of Lambda (so, SD of L would be bigger), but not into bias
> -- and that is what we see; but I can well be wrong about that.
>

You might be right, I've not thought a lot about it, but my initial 
thinking was there might be some bias, my line of thought was: if there 
is maximal uncertainty in K then K adds no useful information, so you'd 
expect to estimate heritability=0, but then your statistics are just 
uncorrected chisq, so you have a standard GC situation in which case 
lambda>1. However if K is accurate you'd hope that the statistic is 
correct therefore lambda=1. But maybe this is not quite what you mean by 
bias?

> I think we can get a better view of the problem and answer to
> William's hypothesis when we get polygenic-FMM working as an entity,

OK, I'll see what I can do. Is the best approach to have the user create 
a Polygenic-FMM R object and then let the user apply an R function to it 
when they want to do the GWAS?

GWAS-FMM(Polygenic-FMM-Object, GWAS-SNP-Data)

In this case we will need to call two separate C functions from R, when 
to setup and fit polygenic-FMM object and then another to run the GWAS.

bw

Will


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