PMR_individual {PPMR} | R Documentation |
Fit the probabilistic MR model with individual level data while accounting for the correlated instruments and horizontal pleiotropy in TWAS framework.
PMR_individual(yin, zin, x1in, x2in, gammain, alphain, max_iterin, epsin)
yin |
standardized exposure vector (e.g. gene expression in TWAS). |
zin |
standardized complex trait vector. |
x1in |
standardized cis-genotype matrix in eQTL data. |
x2in |
standardized cis-genotype matrix in GWAS data. |
gammain |
indicator variable for constrained PMR model, with 1 for the null model that there is no horizontal pleiotropy. |
alphain |
indicator variable for constrained PMR model, with 1 for the null model that there is no causal effect. |
max_iterin |
The maximum iteration. |
epsin |
The convergence tolerance of the absolute value of the difference between the nth and (n+1)th log likelihood. |
a list of estimates of model parameters, including the causal effect
alpha
, the horizontal pleiotropy effect gamma
, and the two
corresponding p values
Zhongshang Yuan, Xiang Zhou.
data(Exampleindividual) attach(Exampleindividual) fmH1 = PMR_individual(yin=x, zin=y, x1in=zx, x2in=zy, gammain=0,alphain = 0,max_iterin =1000,epsin=1e-5) alpha<-fmH1$alpha gamma<-fmH1$gamma fmH0gamma = PMR_individual(yin=x,zin= y, x1in=zx, x2in=zy,gammain=1, alphain = 0,max_iterin =1000,epsin=1e-5) fmH0alpha = PMR_individual(yin=x, zin=y, x1in=zx, x2in=zy,gammain=0, alphain = 1,max_iterin =1000, epsin=1e-5) loglikH1=max(fmH1$loglik,na.rm=TRUE) loglikH0gamma=max(fmH0gamma$loglik,na.rm=TRUE) loglikH0alpha=max(fmH0alpha$loglik,na.rm=TRUE) stat_alpha = 2 * (loglikH1 - loglikH0alpha) pvalue_alpha = pchisq(stat_alpha,1,lower.tail=FALSE) stat_gamma = 2 * (loglikH1 - loglikH0gamma) pvalue_gamma = pchisq(stat_gamma,1,lower.tail=FALSE)