Hi,
I am using a post-gwas analysis tools to test genetic overlap between different traits based on summary level data, and it requires the effect size(beta) and SE.
So for summary stats that has the Z score measures, beta and SE are estimated by using the following formula that was published in a large scale study on Alzheimers.
SE~=sqrt(VP/(ES×2pq))
Beta=SE×Z
where:
- VP: phenotypic variance approximated to 1;
- ES: effective sample size
- pq: allele frequencies (p allele, q allele)
- Z: Z scores
The summary stats that I currently have access to does not have allele frequency information.
head of the summary stats:
> Chr Pos MarkerName EffectAllele OtherAllele Z P.value TotalSampleSize
> 1 744055 rs3131000 a g -1.60 0.10 23546
Is there a way to calculate the Betas and SE without contacting the study, with just relying on the information that is currently publicly available.
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muralinmars •
1 answer
You can use this equation:
Beta = z / sqrt(2p(1− p)(n + z^2)) and
SE =1 / sqrt(2p(1− p)(n + z^2))
Where p is the frequency of the imputed SNP, you could use out reference panel to calculate p. For reference please go to
https://images.nature.com/full/nature-assets/ng/journal/v48/n5/extref/ng.3538-S1.pdf
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Hi, Would it be possible to send the link of the Alzheimers paper you found the equation in please?
I am somewhat pressed for time but it's not 100% clear which data-points you have. Please take a look here and see if you can work back from the Z-score calculation: A: SNP dataset and Z Score
Do you have the allele tallies?