Genetic power calculation: how many individuals will survive p-val correction

Question

[epermina]

Hi, I was trying to wrap my mind around the following question we need to answer: given our experimental design, how many individuals in the study could have p-Val, that will survive a p-Value adjustment? What I have is number of people in case and control groups, MAF, ORs, and the power is 80%. We are treating this as a study of a discrete trait. I had a look at Purcell's GPC, but got confused by D-prime and allele B frequency: what I have is a range of SNP to monitor in a genome-wide association study, is this where my MAF would go? Shook me if I'm dead wrong, I'm very new to genetics stats. Do I get the answer to my question by comparing my sample size to the estimated sample size from a power calculator?

Thank you for your help,

Answer 1

[Carlo Yague]

how many individuals in the study could have p-Val that will survive a p-Value adjustment?

Power is one thing but the stringency of the pvalue adjustment will also depend on the distribution of p-values: if your effect is large, then you'll have many low p-val and the adjustment will not affect them much. But if the effect is subtle, then the pval distribution is more linear and the adjustment is more stringent.

In the end, I don't think one can answer that question before running the experiment.

Hopefully, someone will come up with a more useful answer :)

EDIT : my answer is valid for p-val adjustment methods that control FDR (False Discovery Rate) such as the Benjamini method. However the dependancy on the pvalue distribution doesn't apply to methods that control the ‘family-wise error rate’ such as the Bonferroni correction.

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See : Noble, W. S. (2009). How does multiple testing correction work? Nature Biotechnology, 27(12), 1135–7. doi:10.1038/nbt1209-1135

Answer 2

[natasha.sernova]

I hope these posts will help you:

How To Calculate A Sample Size

Formula Of Power/Sample Size Calculation In Gwas

How To Combine P-Values Obtained With Different Approaches?

There are a lot of statistical questions in biostars.org.

Just press 'LATEST' in the upper left corner, type 'p-value' or 'power'

in the empty line under the menu. Below you will see a list of the light green posts with these words, metioned inside.

Press on the upper left corner of green post you like, and you will see the whole post.

At the same time you will see many posts discussing the issue in the column on the right.