mvSuSiE RSS compare with PAINTOR
Yuxin Zou
02/11/2021
Last updated: 2021-07-12
Checks: 7 0
Knit directory: mmbr-rss-dsc/
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| Rmd | 6697f4a | zouyuxin | 2021-02-11 | add comparison with paintor |
This is result from our mvSuSiE RSS simulation using UKB data. There are 600 datasets. The max PVE across traits is 0.0005.
For each dataset, we simulate 2 signals with independent effects in 2 conditions.
We run mvSuSiE-suff and mvSuSiE-rss with L = 10. We estimate prior weights using ‘EM’ method.
We use PAINTORv3.0 from github. Since we run PAINTOR without any annotations, we create a ‘dummy’ annotation file for each region with all 1’s. Using the mcmc option, the posterior inclusion probability is always 0 in several test dataset. The same issue is reported here. Therefore, we use -enumerate 2 option, which enumerate all possible configurations up to 2 causals in each region.
We compare PIP for each SNP. PAINTOR has very high FDR.
Here is one example:
Z = as.matrix(data.table::fread('data/PAINTOR_problem_2indep/test.PAINTOR', header=TRUE))
B = readRDS('data/PAINTOR_problem_2indep/test.PAINTOR.2indep.rds')
ld = as.matrix(data.table::fread('data/PAINTOR_problem_2indep/test.PAINTOR.ld'))The variable 5, 1035 has non-zero effect in 2 traits.
The z scores at true effects are
Z[c(5,1035),] 1 2
[1,] -9.844684 -6.459602
[2,] 4.076751 -3.336378par(mfrow=c(1,2))
plot(Z[,1], pch=16)
points(c(5, 1035), Z[c(5,1035),1], pch=16, col = 'red')
plot(Z[,2], pch = 16)
points(c(5, 1035), Z[c(5,1035),2], pch=16, col = 'red')
Using mvSuSiE with default prior,
library(ggplot2)
m_init = mvsusieR::create_mash_prior(mixture_prior = list(matrices=mvsusieR:::create_cov_canonical(2), weights=NULL),
null_weight=NULL, max_mixture_len=-1)
m = mvsusieR::mvsusie_rss(Z, R = ld, L=10, prior_variance=m_init,
residual_variance=diag(2),
compute_objective=TRUE,
estimate_prior_variance=T, estimate_prior_method='EM',
precompute_covariances=T, n_thread=1,
max_iter=1000, track_fit = FALSE, verbosity = FALSE)Warning in mvsusie_core(data, s_init, L, prior_variance, prior_weights, :
precompute_covariances option is disabled when prior variances are to be
updated.susieR::susie_plot(m, y = 'PIP', b = B)
From PAINTOR, the PIPs are
paintor_pip = data.table::fread('data/PAINTOR_problem_2indep/test.PAINTOR.results')
plot(paintor_pip$Posterior_Prob, pch=16)
points(c(5, 1035), paintor_pip$Posterior_Prob[c(5, 1035)], pch=16, col='red')
The z scores for SNPs with PIP=1 in PAINTOR are
Z[which(paintor_pip$Posterior_Prob>0.5),] 1 2
[1,] 0.0245403 -1.741608
[2,] -2.2387469 -0.407986
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/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] ggplot2_3.3.5 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] progress_1.2.2 softImpute_1.4-1 tidyselect_1.1.0
[4] xfun_0.22 purrr_0.3.4 ashr_2.2-51
[7] lattice_0.20-41 colorspace_2.0-2 vctrs_0.3.8
[10] generics_0.1.0 htmltools_0.5.1.1 yaml_2.2.1
[13] utf8_1.2.1 rlang_0.4.11 mixsqp_0.3-46
[16] later_1.1.0.1 pillar_1.6.1 glue_1.4.2
[19] withr_2.4.2 DBI_1.1.1 mashr_0.2.49
[22] plyr_1.8.6 matrixStats_0.59.0 lifecycle_1.0.0
[25] stringr_1.4.0 munsell_0.5.0 gtable_0.3.0
[28] mvtnorm_1.1-2 evaluate_0.14 knitr_1.31
[31] httpuv_1.5.5 invgamma_1.1 irlba_2.3.3
[34] fansi_0.5.0 highr_0.8 Rcpp_1.0.7
[37] susieR_0.11.43 promises_1.2.0.1 scales_1.1.1
[40] rmeta_3.0 truncnorm_1.0-8 abind_1.4-5
[43] fs_1.5.0 hms_1.1.0 digest_0.6.27
[46] stringi_1.5.3 dplyr_1.0.5 grid_4.0.3
[49] rprojroot_2.0.2 tools_4.0.3 magrittr_2.0.1
[52] tibble_3.1.2 crayon_1.4.1 whisker_0.4
[55] pkgconfig_2.0.3 ellipsis_0.3.2 Matrix_1.3-2
[58] prettyunits_1.1.1 SQUAREM_2021.1 data.table_1.14.0
[61] reshape_0.8.8 assertthat_0.2.1 rmarkdown_2.7
[64] R6_2.5.0 git2r_0.28.0 compiler_4.0.3
[67] mvsusieR_0.0.3.0436