Probelm set investigate

Last updated: 2019-02-15

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The simulated data has 1 true effects. The PVE is 0.5.

library(kableExtra)
library(knitr)
library(susieR)
library(png)
data = readRDS('data/sim_gaussian_75.rds')
n = data$n
beta = numeric(data$p)
beta[data$beta_idx] = data$beta_val
z = data$ss$effect/data$ss$se
susie_plot(z, y = "z", b=beta)

The true signals are at 386.

dscout = readRDS('output/dscoutProblem75.rds')
fit_susie = readRDS('~/Documents/GitHub/dsc-finemap/output/susie_z_Problem75/susie_z/full_data_1_get_sumstats_1_susie_z_1.rds')

SuSiE z PIP

The model from DAP-G finds 8 credible sets, 1 of them contain true signals.

The 95% confidence set from finemap contains 1000 SNPs, 1 of them are true signals. It prefers the model with 3 causal SNPs. Both finemap and dap have many false positives.

finemap result: A is the posterior of number of causals. B is the probability of different configuration. C is the PIP of the top 10 SNPs.

Comparing the PIP for the true signal:

susie_pip = matrix(as.numeric(dscout[1, 11]), 1,1)
dap_pip = matrix(as.numeric(dscout[3, 19]), 1,1)
finemap_pip = matrix(as.numeric(dscout[4, 24]), 1,1)
tmp = rbind(susie_pip, dap_pip, finemap_pip)
row.names(tmp) = c('susie z', 'dap', 'finemap')
colnames(tmp) = paste0('Signal ', 1)
tmp %>% kable() %>% kable_styling()

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] png_0.1-7         susieR_0.6.4.0438 knitr_1.20        kableExtra_1.0.1 

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0        highr_0.7         pillar_1.3.1     
 [4] compiler_3.5.1    git2r_0.24.0      workflowr_1.1.1  
 [7] R.methodsS3_1.7.1 R.utils_2.7.0     tools_3.5.1      
[10] digest_0.6.18     evaluate_0.12     tibble_2.0.1     
[13] viridisLite_0.3.0 lattice_0.20-38   pkgconfig_2.0.2  
[16] rlang_0.3.1       Matrix_1.2-15     rstudioapi_0.9.0 
[19] yaml_2.2.0        stringr_1.3.1     httr_1.4.0       
[22] xml2_1.2.0        hms_0.4.2         rprojroot_1.3-2  
[25] webshot_0.5.1     grid_3.5.1        glue_1.3.0       
[28] R6_2.3.0          rmarkdown_1.11    readr_1.3.1      
[31] magrittr_1.5      whisker_0.3-2     backports_1.1.3  
[34] scales_1.0.0      htmltools_0.3.6   rvest_0.3.2      
[37] colorspace_1.4-0  stringi_1.2.4     munsell_0.5.0    
[40] crayon_1.3.4      R.oo_1.22.0      

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