Last updated: 2021-03-10
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Canonical patterns of sharing:
R = 20
prior = mmbr:::create_cov_canonical(R)Paired sharing:
paired = matrix(0,R,R)
paired[1:2,1:2] = 1
prior[['paired_1']] = paired
paired = matrix(0,R,R)
paired[10:11,10:11] = 1
prior[['paired_2']] = pairedBlock sharing:
block = matrix(0,R,R)
block[1:R/2, 1:R/2] = 1
block[(R/2+1):R, (R/2+1):R] = 1
prior[['blocked_1']] = blockWe assign weights to priors:
singleton total 25%
singleton_1 has 15%
singleton_2 to singleton_11 has 10% (1% each)
shared total 25%
paired 30% (15% each)
blocked 20%
w = c(0.15, rep(0.01, 10), rep(0, 9), rep(0.05, 5), rep(0.15,2), 0.2)prior = prior[which(w>0)]
w = w[which(w>0)]
artificial_mixture_20 = list(U=prior,w=w)Canonical patterns of sharing:
R = 4
prior = mmbr:::create_cov_canonical(R)Paired sharing:
paired = matrix(0,R,R)
paired[1:2,1:2] = 1
prior[['paired_1']] = pairedBlock sharing:
block = matrix(0,R,R)
block[1:R/2, 1:R/2] = 1
block[(R/2+1):R, (R/2+1):R] = 1
prior[['blocked_1']] = blockWe assign weights to priors:
singleton total 30%
shared total 50%
paired 10%
blocked 10%
w = c(0.15, 0.15, 0, 0, rep(0.5/5,5), 0.1, 0.1)prior = prior[which(w>0)]
names(prior)[1] "singleton_1" "singleton_2" "shared_1" "shared_2" "shared_3"
[6] "shared_4" "shared_5" "paired_1" "blocked_1" w = w[which(w>0)]
artificial_mixture_4 = list(U=prior,w=w)Canonical patterns of sharing:
R = 2
prior = mmbr:::create_cov_canonical(R)We assign weights to priors:
singleton total 40%
shared total 60%
w = c(0.2, 0.2, rep(0.6/5,5))prior = prior[which(w>0)]
names(prior)[1] "singleton_1" "singleton_2" "shared_1" "shared_2" "shared_3"
[6] "shared_4" "shared_5" w = w[which(w>0)]
artificial_mixture_2 = list(U=prior,w=w)The priors are from this workflow.
prior = readRDS('~/Documents/GitHub/finemap-uk-biobank/output/BloodCells.Ulist.Scor.ed.rds')
names(prior$U) [1] "FLASH_1" "FLASH_2" "FLASH_3" "FLASH_4" "FLASH_5" "FLASH_6"
[7] "FLASH_7" "FLASH_8" "FLASH_9" "FLASH_10" "FLASH_11" "FLASH_12"
[13] "FLASH_13" "tFLASH" "PCA_1" "PCA_2" "PCA_3" "tPCA"
[19] "XX" Most weighths are in tFLASH and XX,
names(prior$U)[prior$w>0.1][1] "tFLASH" "XX" But many other weights are also non-trivial
names(prior$U)[prior$w > 0.001] [1] "FLASH_1" "FLASH_2" "FLASH_3" "FLASH_4" "FLASH_5" "FLASH_6"
[7] "FLASH_7" "FLASH_8" "FLASH_9" "FLASH_10" "FLASH_12" "FLASH_13"
[13] "tFLASH" "tPCA" "XX" tol=1E-12
U = prior$U[which(prior$w>tol)]
w = prior$w[which(prior$w>tol)]
names(U) [1] "FLASH_1" "FLASH_2" "FLASH_3" "FLASH_4" "FLASH_5" "FLASH_6"
[7] "FLASH_7" "FLASH_8" "FLASH_9" "FLASH_10" "FLASH_12" "FLASH_13"
[13] "tFLASH" "PCA_3" "tPCA" "XX" bloodcells_mixture = list(U=U,w=w)for(i in 1:length(U)){
bloodcells_mixture$U[[i]] = (bloodcells_mixture$U[[i]] + t(bloodcells_mixture$U[[i]]))/2
eigenU = eigen(bloodcells_mixture$U[[i]], symmetric = T)
if(any(eigenU$values<0)){
eigenU$values[eigenU$values < 0] = 0
bloodcells_mixture$U[[i]] = eigenU$vectors %*% (t(eigenU$vectors) * eigenU$values)
}
}saveRDS(list(bloodcells_mixture=bloodcells_mixture, artificial_mixture_20=artificial_mixture_20, artificial_mixture_4=artificial_mixture_4, artificial_mixture_2 = artificial_mixture_2), 'output/ukb_prior_simulation.rds')
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] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] progress_1.2.2 tidyselect_1.1.0 xfun_0.19 ashr_2.2-51
[5] purrr_0.3.4 lattice_0.20-41 colorspace_2.0-0 vctrs_0.3.6
[9] generics_0.1.0 htmltools_0.5.0 yaml_2.2.1 rlang_0.4.10
[13] mixsqp_0.3-46 later_1.1.0.1 pillar_1.4.7 glue_1.4.2
[17] plyr_1.8.6 matrixStats_0.58.0 lifecycle_1.0.0 stringr_1.4.0
[21] munsell_0.5.0 gtable_0.3.0 mvtnorm_1.1-1 evaluate_0.14
[25] knitr_1.30 httpuv_1.5.4 invgamma_1.1 irlba_2.3.3
[29] Rcpp_1.0.6 promises_1.1.1 scales_1.1.1 susieR_0.10.0
[33] truncnorm_1.0-8 abind_1.4-5 fs_1.5.0 ggplot2_3.3.3
[37] hms_1.0.0 digest_0.6.27 stringi_1.5.3 dplyr_1.0.2
[41] mmbr_0.0.2.0429 grid_4.0.3 rprojroot_2.0.2 tools_4.0.3
[45] magrittr_2.0.1 tibble_3.0.6 crayon_1.4.1 whisker_0.4
[49] pkgconfig_2.0.3 ellipsis_0.3.1 Matrix_1.2-18 SQUAREM_2021.1
[53] prettyunits_1.1.1 rmarkdown_2.5 reshape_0.8.8 R6_2.5.0
[57] git2r_0.27.1 compiler_4.0.3