Last updated: 2020-05-28

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library(mr.ash.alpha)
source("~/causalTWAS/causal-TWAS/code/fit_mr.ash.R")

summary_mr.ash <- function(fit){
  cat("pi1 = ", 1-fit$pi[[1]], "\n")
  pve <- get_pve(fit)
  cat("pve = ", pve, "\n")
}

plot_beta <- function(beta,beta.pm, ...){
  plot( beta, pch=19, col ="darkgreen", ...)
  points(beta.pm, pch =19, col = "red")
  legend("topright", legend=c("true beta", "posterior mean"),
       col=c("darkgreen", "red"), pch=19)
}

plot_pip <- function(indi, pip, pipcut = 0.1) {
  x <- barplot(indi, main = "PIP")
  points(x, pip, pch=19, col="red")
  pred <- which(pip > pipcut)
  real <- which(indi==1)
  tp <- length(intersect(pred, real))/length(pred)
  fp <- 1 - tp
  fn <- length(setdiff(real, pred))/length(real)
  cat("false positive rate: ", fp, "\n")
  cat("false negative rate: ", fn, "\n")
}

summary_mr.ash2 <- function(g.fit, s.fit, phenores, pipcut = 0.1){
  e.b <- rep(0, length(g.fit$beta))
  e.b[phenores$param$idx.cgene] <- phenores$param$e.beta
  cat("gene expression effect: \n")
  summary_mr.ash(g.fit)
  plot_beta(e.b, g.fit$beta)
  indi <- rep(0, length(g.fit$beta))
  indi[phenores$param$idx.cgene] <- 1
  pip <- get_pip(g.fit)
  plot_pip(indi, pip, pipcut = pipcut)
  
  s.b <- rep(0, length(s.fit$beta))
  s.b[phenores$param$idx.cSNP] <- phenores$param$s.theta
  cat("snp effect: \n")
  summary_mr.ash(s.fit)
  plot_beta(s.b, s.fit$beta)
}
simdatadir <- "~/causalTWAS/simulations/simulation_ashtest_20200503/"
outputdir <- "~/causalTWAS/simulations/simulation_ashtest_20200527/"

Simulation 1

True parameters:

load(paste0(simdatadir, "mr.ash2_20200503-1-pheno.Rd"))
readLines(paste0(simdatadir, "param-20200503-1.R"))
[1] "pve.expr <- 0.01" "pve.snp <- 0.05"  "pi_beta <-  0.1" 
[4] "pi_theta <- 1e-3" "tau <- 1"

MR.ASH2s results (start from gene):

load(paste0(outputdir, "20200527-1-mr.ash2s.expr-res.Rd"))
g.fit <- mr.ash2s.fit$fit1
s.fit <-  mr.ash2s.fit$fit2
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  0.05417903 
pve =  0.1336998 

false positive rate:  0.3 
false negative rate:  0.4615385 
snp effect: 
pi1 =  0.0001887495 
pve =  0.2500488

MR.ASH results (start from SNP):

load(paste0(outputdir, "20200527-1-mr.ash2s.snp-res.Rd"))
g.fit <- mr.ash2s.fit$fit2
s.fit <-  mr.ash2s.fit$fit1
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  0.05417931 
pve =  0.1337004 

false positive rate:  0.3 
false negative rate:  0.4615385 
snp effect: 
pi1 =  0.0001887502 
pve =  0.2500495

Simulation 2

True parameters:

load(paste0(simdatadir, "mr.ash2_20200503-2-pheno.Rd"))
readLines(paste0(simdatadir, "param-20200503-2.R"))
[1] "pve.expr <- 0.005" "pve.snp <- 0.01"   "pi_beta <-  0.1"  
[4] "pi_theta <- 1e-3"  "tau <- 1"

MR.ASH results (start from gene):

load(paste0(outputdir, "20200527-2-mr.ash2s.expr-res.Rd"))
g.fit <- mr.ash2s.fit$fit1
s.fit <-  mr.ash2s.fit$fit2
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  1.973726e-10 
pve =  7.959401e-08 

false positive rate:  NaN 
false negative rate:  1 
snp effect: 
pi1 =  1.115821e-07 
pve =  0.0002921814

MR.ASH results (start from SNP):

load(paste0(outputdir, "20200527-2-mr.ash2s.snp-res.Rd"))
g.fit <- mr.ash2s.fit$fit2
s.fit <-  mr.ash2s.fit$fit1
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  1.966005e-10 
pve =  7.958468e-08 

false positive rate:  NaN 
false negative rate:  1 
snp effect: 
pi1 =  1.196675e-07 
pve =  0.0003063728

Simulation 3

True parameters:

load(paste0(simdatadir, "mr.ash2_20200503-3-pheno.Rd"))
readLines(paste0(simdatadir, "param-20200503-3.R"))
[1] "pve.expr <- 0.01" "pve.snp <- 0.05"  "pi_beta <-  0.05"
[4] "pi_theta <- 1e-4" "tau <- 1"

MR.ASH results (start from gene):

load(paste0(outputdir, "20200527-3-mr.ash2s.expr-res.Rd"))
g.fit <- mr.ash2s.fit$fit1
s.fit <-  mr.ash2s.fit$fit2
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  0.02753678 
pve =  0.07367684 

false positive rate:  0.3333333 
false negative rate:  0.7142857 
snp effect: 
pi1 =  0.0001530549 
pve =  0.2156009

MR.ASH results (start from SNP):

load(paste0(outputdir, "20200527-3-mr.ash2s.snp-res.Rd"))
g.fit <- mr.ash2s.fit$fit2
s.fit <-  mr.ash2s.fit$fit1
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  0.009105761 
pve =  0.02562701 

false positive rate:  0 
false negative rate:  0.8571429 
snp effect: 
pi1 =  0.0001684206 
pve =  0.2321756

Simulation 4

True parameters:

load(paste0(simdatadir, "mr.ash2_20200503-4-pheno.Rd"))
readLines(paste0(simdatadir, "param-20200503-4.R"))
[1] "pve.expr <- 0.005" "pve.snp <- 0.01"   "pi_beta <-  0.05" 
[4] "pi_theta <- 1e-4"  "tau <- 1"

MR.ASH results (start from gene):

load(paste0(outputdir, "20200527-4-mr.ash2s.expr-res.Rd"))
g.fit <- mr.ash2s.fit$fit1
s.fit <-  mr.ash2s.fit$fit2
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  0.03483871 
pve =  0.09146919 

false positive rate:  0.5 
false negative rate:  0.7142857 
snp effect: 
pi1 =  4.177662e-05 
pve =  0.0699035

MR.ASH results (start from SNP):

load(paste0(outputdir, "20200527-4-mr.ash2s.snp-res.Rd"))
g.fit <- mr.ash2s.fit$fit2
s.fit <-  mr.ash2s.fit$fit1
summary_mr.ash2(g.fit, s.fit, phenores)
gene expression effect: 
pi1 =  0.02582045 
pve =  0.06943356 

false positive rate:  0.3333333 
false negative rate:  0.7142857 
snp effect: 
pi1 =  5.635395e-05 
pve =  0.09201309 


sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] mr.ash.alpha_0.1-7

loaded via a namespace (and not attached):
 [1] workflowr_1.6.0 Rcpp_1.0.4.6    lattice_0.20-38 digest_0.6.18  
 [5] later_0.7.5     rprojroot_1.3-2 grid_3.5.1      R6_2.3.0       
 [9] backports_1.1.2 git2r_0.26.1    magrittr_1.5    evaluate_0.12  
[13] highr_0.7       stringi_1.3.1   fs_1.3.1        promises_1.0.1 
[17] Matrix_1.2-15   rmarkdown_1.10  tools_3.5.1     stringr_1.4.0  
[21] glue_1.3.0      httpuv_1.4.5    yaml_2.2.0      compiler_3.5.1 
[25] htmltools_0.3.6 knitr_1.20