I hear Polygenic Risk Score (PRS) recently by reading the PRSice-2 paper. PRS is simple but interesting. There are few questions on PRS and the tool, could anyone help?
1, In my understanding, PRSice-2 scores new individual/population by summing up the effect sizes of the effect alleles from previous GWAS. However, there are at least two different ways to do GWAS, including single-SNP association test which considers each SNP independently as fixed effect and mixed linear model test which considers all SNPs simultaneously as random effect. The effect size estimated by the two methods differ remarkably. So, which association analysis method is recommended for subsequent PRS calculation?
2, How often is the PRS used for non-additive model GWAS (i.e GWAS under dominant/recessive model)? If I understand correctly, PRS can be used for predicting phenotypes, so is it equivalent to the Genomic BLUP? (i.e. GWAS + PRS = training + prediction = Genomic BLUP).
3, Is it SNP effect size (beta) same as SNP heritability? Could I find the definition of effective allele? Is the effect size of non-effective allele 0 by definition?
4, By playing with the example file in the PRSice zip file using the command below:
./PRSice_linux -b TOY_BASE_GWAS.assoc -t TOY_TARGET_DATA --or --binary-target T
it generates an output file "PRSice.best" in which I believe the phenotype predictions are recorded. It looks like:
FID IID In_Regression PRS CAS_1 CAS_1 Yes -0.00599501328 CAS_2 CAS_2 Yes -0.00631017938 CAS_3 CAS_3 Yes -0.00227495325 CAS_4 CAS_4 Yes -0.00204360007 CAS_5 CAS_5 Yes -0.000830676955
I expect the PRS is the continuous phenotype value or binary outcome of the individual in the target data. But how could I convert the PRS values here into binary outcome?