Last updated: 2020-08-05
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Knit directory: gene_level_fine_mapping/
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load("/Users/nicholeyang/Desktop/Rotation2/data/hic_eqtl.RData")hic_eqtl2 = hic_eqtl[!is.na(hic_eqtl$baitName), ]
bait_gene = strsplit(as.character(hic_eqtl2$baitName), ';')
ngenes = lapply(bait_gene, function(x) length(x))
index_list = c()
for(i in 1:dim(hic_eqtl2)[1]){
index = rep(i, ngenes[[i]])
index_list = c(index_list, index)
}
hic_eqtl3 = hic_eqtl2[index_list, ]
hic_eqtl3$bait_gene = unlist(bait_gene)load("/Users/nicholeyang/Desktop/gene_level_fine_mapping/data/training.RData")
## remove NAs
dat = rbind(train_pos_all, train_neg_all)
NAs = apply(dat, 1, function(x) sum(is.na(x)))
dat = dat[NAs == 0, ]var_loc = strsplit(as.character(dat$variant_id), '_')
dat$snp_loc38 = paste(unlist(lapply(var_loc, function(x) x[1])), unlist(lapply(var_loc, function(x) x[2])), sep = ':')var_loc = strsplit(as.character(hic_eqtl3$loc_38map), '-')
hic_eqtl3$snp_loc38 = unlist(lapply(var_loc, function(x) x[1]))## restrict to coding gene
coding_gene_list = read.table('/Users/nicholeyang/Desktop/Rotation2/data/coding_gene_list.txt', header = TRUE)
coding_gene_list$bait_gene = coding_gene_list$Approved_symbol
hic_eqtl4 = merge(coding_gene_list, hic_eqtl3, by = 'bait_gene', all = FALSE)
colnames(hic_eqtl4)[1] = 'gene_name'tail(dat) gene_name variant_id UTR5 UTR3 exon intron upstream
121265 SEC61B chr9_99153605_C_T_b38 0 0 0 0 0
49988 GALNT12 chr9_99153605_C_T_b38 0 0 0 0 0
4837 ALG2 chr9_99153605_C_T_b38 0 0 0 0 0
49602 GABBR2 chr9_99153605_C_T_b38 0 0 0 0 0
6225 ANKS6 chr9_99153605_C_T_b38 0 0 0 0 0
28348 COL15A1 chr9_99153605_C_T_b38 0 0 0 0 0
tss_dist_to_snp y snp_loc38
121265 68696 0 chr9:99153605
49988 345906 0 chr9:99153605
4837 67535 0 chr9:99153605
49602 444408 0 chr9:99153605
6225 357066 0 chr9:99153605
28348 209966 0 chr9:99153605Among all the gene-snp pairs, ~9500 hic features are added.
index_in_hic = c()
for(i in 1:dim(dat)[1]){
index = which(dat[i, ]$gene_name == hic_eqtl4$gene_name & dat[i, ]$snp_loc38 == hic_eqtl4$snp_loc38)
index_in_hic = c(index_in_hic, index)
}
train_hic = hic_eqtl4[index_in_hic, c("gene_name", "Mon", "Mac0", "Mac1", "Mac2", "Neu",
"MK", "EP", "Ery", "FoeT", "nCD4", "tCD4", "aCD4",
"naCD4", "nCD8", "tCD8", "nB", "tB","snp_loc38")]
dat_add_hic = merge(dat, train_hic, by = c('gene_name', 'snp_loc38'), all = TRUE)## check NAs
Nas = apply(dat_add_hic, 2, function(x) sum(is.na(x)))
Nas gene_name snp_loc38 variant_id UTR5 UTR3
0 0 0 0 0
exon intron upstream tss_dist_to_snp y
0 0 0 0 0
Mon Mac0 Mac1 Mac2 Neu
57448 57448 57448 57448 57448
MK EP Ery FoeT nCD4
57448 57448 57448 57448 57448
tCD4 aCD4 naCD4 nCD8 tCD8
57448 57448 57448 57448 57448
nB tB
57448 57448 ## replace NAs with 0
dat_add_hic[is.na(dat_add_hic)] <- 0## binary the hic features
cols = c("Mon", "Mac0", "Mac1", "Mac2", "Neu", "MK", "EP", "Ery", "FoeT",
"nCD4", "tCD4", "aCD4", "naCD4", "nCD8", "tCD8", "nB", "tB")
for( i in 1:length(cols)){
dat_add_hic[, cols[i]] = ifelse(as.numeric(as.character(dat_add_hic[, cols[i]])) >=5, 1, 0)
}
save(dat_add_hic, file = '/Users/nicholeyang/Desktop/gene_level_fine_mapping/data/train_add_hic.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