PRS_Dis_LDpred2 {PRSPGx} | R Documentation |
Construct disease PRS using LDpred2
Description
Using snp_ldpred2_grid function from bigsnpr function
Usage
PRS_Dis_LDpred2(DIS_GWAS, G_reference, pcausal, h2)
Arguments
DIS_GWAS |
a numeric matrix containing disease GWAS summary statistics, including SNP ID, position, |
G_reference |
a numeric matrix containing the individual-level genotype information from the reference panel (e.g., 1KG) |
pcausal |
a numeric value indicating the hyper-parameter as the proportion of causal variants |
h2 |
a numeric value indicating the estimated heritability |
Details
PRS-Dis-LDpred2 automatically sets predictive effect sizes equivalent to the prognostic effect sizes; and only need disease GWAS summary statistics and external reference genotype
Value
A numeric list, the first sublist contains estimated prognostic effect sizes, the second sublist contains estimated predictive effect sizes
Author(s)
Song Zhai
References
Prive, F., Arbel, J. & Vilhjalmsson, B.J. LDpred2: better, faster, stronger. Bioinformatics 36, 5424-5431 (2020).
Zhai, S., Zhang, H., Mehrotra, D.V. & Shen, J. Paradigm Shift from Disease PRS to PGx PRS for Drug Response Prediction using PRS-PGx Methods (submitted).
Examples
data(PRSPGx.example); attach(PRSPGx.example)
coef_est <- PRS_Dis_LDpred2(DIS_GWAS, G_reference, pcausal = 0.1, h2 = 0.4)
summary(coef_est$coef.G)
summary(coef_est$coef.TG)