Last updated: 2020-07-10
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Knit directory: gene-level fine mapping/
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# unix command
srun --pty --mem 5G -t 01:00:00 /bin/bash
module load R
Rsetwd("/home/yunqiyang/summer_rotation/whole_blood_eqtl")
dt = read.table("Whole_Blood.variants_pip.txt", header = TRUE)
dim(dt) # 420370 6
sum(is.na(dt)) # 0setEPS()
postscript("pip_summary.eps")
hist(dt$pip)
dev.off()length(unique(dt$gene)) # 15252
sum(dt$pip>0.5) # 5080
sum(dt$pip>0.8) # 2751
sum(dt$pip>0.1) # 28559# save data
dt_pos = dt[dt$pip>0.5, ]
dt_neg = dt[-(dt$pip>0.5), ]
save(dt_pos, file = 'SNPs_causal.RData')
save(dt_neg, file = 'SNPs_control.RData')# load fine-mapping positive set
load("/Users/nicholeyang/Desktop/Rotation2/gene-level fine mapping/data/SNPs_causal.RData")dt_pos$variant_id = as.character(dt_pos$variant_id)
var_position = strsplit(dt_pos$variant_id, '_')
chr = rep(NA, length(var_position))
SNP_loc = rep(NA, length(var_position))
for (i in 1:length(var_position)){
chr[i] = var_position[[i]][1]
SNP_loc[i] = var_position[[i]][2]
}chr = unlist(lapply(var_position, function(x) x[1]))
dt_pos$SNP_chr = gsub('\\D','', chr)
dt_pos$SNP_loc = unlist(lapply(var_position, function(x) x[2]))gene_seg = strsplit(as.character(dt_pos$gene), '.', fixed = TRUE)
dt_pos$gene_id = unlist(lapply(gene_seg, function(x) x[1]))head(dt_pos) gene rank variant_id pip log10_abf
5 ENSG00000000457.13 1 chr1_169891332_G_A_b38 0.939551 20.142
43 ENSG00000000460.16 1 chr1_169661963_G_A_b38 0.580082 5.656
307 ENSG00000001561.6 1 chr6_46130021_C_G_b38 0.657995 5.590
308 ENSG00000001561.6 2 chr6_46129743_G_GT_b38 0.513630 22.020
418 ENSG00000001629.9 1 chr7_92245996_C_T_b38 0.520558 7.253
594 ENSG00000002016.17 1 chr12_949572_C_G_b38 0.522047 23.668
cluster_id SNP_chr SNP_loc gene_id
5 1 1 169891332 ENSG00000000457
43 1 1 169661963 ENSG00000000460
307 2 6 46130021 ENSG00000001561
308 3 6 46129743 ENSG00000001561
418 1 7 92245996 ENSG00000001629
594 2 12 949572 ENSG00000002016save(dt_pos, file = 'dt_pos_processed.RData')
sessionInfo()R version 3.6.3 (2020-02-29)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.5
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/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_1.6.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.4 rprojroot_1.3-2 digest_0.6.25 later_1.0.0
[5] R6_2.4.1 backports_1.1.5 git2r_0.26.1 magrittr_1.5
[9] evaluate_0.14 highr_0.8 stringi_1.4.6 rlang_0.4.5
[13] fs_1.3.2 promises_1.1.0 whisker_0.4 rmarkdown_2.1
[17] tools_3.6.3 stringr_1.4.0 glue_1.3.2 httpuv_1.5.2
[21] xfun_0.12 yaml_2.2.1 compiler_3.6.3 htmltools_0.4.0
[25] knitr_1.28