Last updated: 2019-03-03

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library(susieR)
X = readRDS('data/random_data_31.rds')$X
R = cor(X)
data = readRDS('data/random_data_31_sim_gaussian_35.rds')
y = data$Y
beta = data$meta$true_coef
sumstats = readRDS('data/random_data_31_sim_gaussian_35_get_sumstats_1.rds')
zscores = sumstats$sumstats$bhat/sumstats$sumstats$shat
plot(zscores, pch=16, main='z scores')
pos = 1:length(zscores)
points(pos[beta!=0],zscores[beta!=0],col=2,pch=16)

Expand here to see past versions of unnamed-chunk-1-1.png:
Version Author Date
34a380e zouyuxin 2019-03-03 

susie_plot(zscores, y = "z", b = beta, main='p values from z scores')

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Version Author Date
34a380e zouyuxin 2019-03-03

We randomly generated 1200 by 1000 matrix X, each entry is random from N(0,1). The variables are independent. There are 5 signals in the simulated data, total PVE is 0.8. The true signals are 424, 427, 523, 941, 950.

fit_z = susie_z(zscores, R, track_fit = TRUE)
susie_plot(fit_z, y='PIP', b=beta)

Expand here to see past versions of unnamed-chunk-2-1.png:
Version Author Date
34a380e zouyuxin 2019-03-03

Using susie z, we only find one signal.

The estimated prior variances are

Vs = matrix(0, 5, 10)
residual_variance = numeric(5)
for(i in 1:length(fit_z$trace)){
  Vs[i,] = fit_z$trace[[i]]$V
  residual_variance[i] = fit_z$trace[[i]]$sigma2
}
Vs[5, ] = fit_z$V
residual_variance[5] = fit_z$sigma2
row.names(Vs) = paste0('Iter ', 1:5)
colnames(Vs) = paste0('L', 1:10)

cbind(Vs, residual_variance)
             L1       L2       L3       L4  L5  L6  L7  L8  L9 L10
Iter 1    0.200  0.20000  0.20000  0.20000 0.2 0.2 0.2 0.2 0.2 0.2
Iter 2 2544.129 44.74233 31.44751 26.07864 0.0 0.0 0.0 0.0 0.0 0.0
Iter 3 2525.683 37.14874  0.00000  0.00000 0.0 0.0 0.0 0.0 0.0 0.0
Iter 4 2542.716 37.02038  0.00000  0.00000 0.0 0.0 0.0 0.0 0.0 0.0
Iter 5 2541.647 36.99735  0.00000  0.00000 0.0 0.0 0.0 0.0 0.0 0.0
       residual_variance
Iter 1          1.000000
Iter 2          2.306961
Iter 3          2.372394
Iter 4          2.373581
Iter 5          2.373607

The result from DAP is DAP result.

Session information

sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14.3

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
[1] susieR_0.6.4.0454

loaded via a namespace (and not attached):
 [1] workflowr_1.1.1   Rcpp_1.0.0        lattice_0.20-38  
 [4] digest_0.6.18     rprojroot_1.3-2   R.methodsS3_1.7.1
 [7] grid_3.5.1        backports_1.1.3   git2r_0.24.0     
[10] magrittr_1.5      evaluate_0.12     stringi_1.2.4    
[13] whisker_0.3-2     R.oo_1.22.0       R.utils_2.7.0    
[16] Matrix_1.2-15     rmarkdown_1.11    tools_3.5.1      
[19] stringr_1.3.1     yaml_2.2.0        compiler_3.5.1   
[22] htmltools_0.3.6   knitr_1.20

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