How to adjust the proportion of SNPs with no additive effect ? about bayesr HOT 3 CLOSED

In BayesB each SNP has its own variance and such models are not implemented in BayesR.
Check out the chapter by Fernando and Garrick in "Genome-Wide Association Studies and Genomic Prediction" for R code of BayesB.

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In BayesR 84% of SNPs has variance 0 from the result I ran and 95% of SNPs has no effect in BayesB. What is the difference I did not notice?
I just want to adjust the proportion of SNPs with no effect, so that the two model are comparable. In other word, if possible to adjust some paremeter in BayesR, giving more wegith for first distribution as prior information, so that the proportation of SNPs with variance 0 reach 95% ?

The parameter "delta", prior for Dirichlet , affect the proportion of SNPs effect. But I am not sure the prior inforatmtin can affect the final result ? Or do not affect the reuslt but only the convergence speed?

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This was a good question:
The parameter "delta", prior for Dirichlet , affect the proportion of SNPs effect. But I am not sure the prior inforatmtin can affect the final result ? Or do not affect the reuslt but only the convergence speed?

It would be nice to know more.

from bayesr.