Blood cells Strong signal patterns
Yuxin Zou
12/1/2020
Last updated: 2020-12-30
Checks: 7 0
Knit directory: finemap-uk-biobank/
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library(data.table)
library(flashr)
library(mixsqp)
library(udr)- Extract 1 snp per region with the strongest signal
regions = fread('/project2/mstephens/yuxin/ukb-bloodcells/regions.csv')
colnames(regions) = c('chr', 'start', 'end', 'length', 'maxlog10p', 'numsnps')
z.strong = c()
z.random = c()
set.seed(2020)
for (i in 1:nrow(regions)){
dat = readRDS(paste0('/project2/mstephens/yuxin/ukb-bloodcells/zscores/bloodcells_chr',
regions$chr[i], '.', regions$start[i], '.', regions$end[i],'.z.rds'))
z = dat$Z
strong.id = which.max(apply(abs(z), 1, max))
z.strong = rbind(z.strong, z[strong.id, ])
null.id = which(apply(abs(z), 1, max) < 2)
random_idx = sample(null.id, 1, replace = F)
z.random = rbind(z.random, z[random_idx,])
}- PCA
par(mfrow=c(1,3))
res.svd = svd(z.strong,nv=3,nu=3)
f = res.svd$v
rownames(f) = colnames(z.strong)
U.pca = mashr:::cov_from_factors(t(f), "PCA")
d = diag(res.svd$d[1:3])
U.pca = c(U.pca, list("tPCA"= f %*% d^2 %*% t(f)/nrow(z.strong)))
for(i in 1:3){
barplot(f[,i], cex.names = 0.7,
las = 2, main = paste0("EigenVector ", i, ' pve: ', round(res.svd$d[i]^2/sum(res.svd$d^2), 3)))
}
| Version | Author | Date |
|---|---|---|
| 0b25399 | zouyuxin | 2020-12-16 |
- FLASH
f.d = flash_set_data(as.matrix(z.strong))
f = flashr::flash(f.d, greedy=TRUE, backfit = T)
saveRDS(f, 'output/BloodCells.flash.model.rds')f = readRDS('output/BloodCells.flash.model.rds')
nonunique_effects <- function(fl) {
thresh <- 1/sqrt(ncol(fl$fitted_values))
vals_above_avg <- colSums(fl$ldf$f > thresh)
nonuniq_effects <- which(vals_above_avg > 1)
return(nonuniq_effects)
}
nonunique_effects_id = nonunique_effects(f)
par(mfrow=c(2,3))
for(i in 1:13){
barplot(f$ldf$f[,i], cex.names = 0.7,
las = 2, main = paste0("Flash factor ", i, " pve: ", round(f$pve[i], 2)))
}
| Version | Author | Date |
|---|---|---|
| 0b25399 | zouyuxin | 2020-12-16 |
| Version | Author | Date |
|---|---|---|
| 0b25399 | zouyuxin | 2020-12-16 |
| Version | Author | Date |
|---|---|---|
| 0b25399 | zouyuxin | 2020-12-16 |
U.flash = c(mashr:::cov_from_factors(t(as.matrix(f$ldf$f)), "FLASH"),
list("tFLASH" = t(f$fitted_values) %*% f$fitted_values / nrow(f$fitted_values)))
Ulist = c(U.flash, U.pca, list("XX" = t(as.matrix(z.strong)) %*% as.matrix(z.strong) / nrow(z.strong)))
saveRDS(Ulist, 'output/BloodCells.flash.pca.ulist.rds')
z.random.cov = cov(z.random)
traits = fread('/project2/mstephens/yuxin/ukb-bloodcells/bloodcells.pheno.resid.txt')
Ycov = cov(traits[,3:18])
saveRDS(list(z.random.cov = z.random.cov, Y.cov = Ycov), 'output/BloodCells.cov.rds')library(udr)
f0 = ud_init(X = as.matrix(z.strong), V = cov2cor(Ycov), U_scaled = list(), U_unconstrained = Ulist, n_rank1=0)
res = ud_fit(f0, control = list(unconstrained.update = "ed", resid.update = 'none', maxiter=5000, minval=1e-12),
verbose=FALSE)
saveRDS(res, 'output/BloodCells.Ulist.Scor.ed.rds')ED weights:
fit.ed = readRDS('output/BloodCells.Ulist.Scor.ed.rds')
barplot(fit.ed$w, las=2, cex.names = 0.7)
sessionInfo()R version 3.6.1 (2019-07-05)
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] udr_0.3-29 mixsqp_0.3-46 flashr_0.6-7 data.table_1.12.8
[5] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] softImpute_1.4 tidyselect_1.1.0 xfun_0.8 ashr_2.2-51
[5] purrr_0.3.4 reshape2_1.4.3 lattice_0.20-38 colorspace_2.0-0
[9] vctrs_0.3.6 htmltools_0.3.6 yaml_2.2.0 rlang_0.4.9
[13] later_0.8.0 pillar_1.4.7 glue_1.4.2 lifecycle_0.2.0
[17] plyr_1.8.6 mashr_0.2.40 stringr_1.4.0 munsell_0.5.0
[21] gtable_0.3.0 mvtnorm_1.1-1 evaluate_0.14 knitr_1.23
[25] httpuv_1.5.1 invgamma_1.1 irlba_2.3.3 Rcpp_1.0.5
[29] promises_1.0.1 scales_1.1.1 rmeta_3.0 abind_1.4-5
[33] truncnorm_1.0-8 fs_1.3.1 ggplot2_3.3.2 digest_0.6.27
[37] stringi_1.4.6 dplyr_0.8.3 ebnm_0.1-24 grid_3.6.1
[41] rprojroot_2.0.2 tools_3.6.1 magrittr_2.0.1 tibble_3.0.4
[45] crayon_1.3.4 whisker_0.3-2 pkgconfig_2.0.3 ellipsis_0.3.1
[49] Matrix_1.2-18 SQUAREM_2020.5 assertthat_0.2.1 rmarkdown_1.13
[53] R6_2.5.0 git2r_0.26.1 compiler_3.6.1