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MR_weak_instrument.R
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library(TwoSampleMR)#Wald ratio,Weighted median,Weighted mode
library(data.table)
library(vcfR)
library(stringr)
library(dplyr)
library(MRPRESSO)#mr_presso
library(mr.raps)#mr raps
library(MendelianRandomization)
library(readxl)
data_res_2 <- read_xlsx('cancer_1/data/check/Main_result.xlsx')
cancer_list <- unique(data_res_2$outcome)
data_res <- read_xlsx('cancer_1/data/check/NC_IV_final.xlsx')
fil_list <- c('ieu-a-1126',
'ieu-b-85',
'ieu-a-966',
'ieu-a-1120',
'thyroid_cancer',
'cervix_cancer')
IV_data_list <- list.files('cancer_1/data/exposure_use_iv_exposure_associations/')
data_res$celltype <- str_split_fixed(data_res$exposure,'_',2)[,2]
weak_IV_list <- list()
for(i in 1:46){
IV <- read.csv(paste0('cancer_1/data/exposure_use_iv_exposure_associations/',IV_data_list[i]))
IV$celltype <- gsub('_500kb_combined_rsID_IV.csv','',IV_data_list[i])
IV$exposure <- paste(IV$exposure,IV$celltype,sep = '_')
weak_IV_list[[i]] <- IV
}
weak_IV_data <- do.call(rbind,weak_IV_list)
for(j in 6){
load(paste0('cancer_1/data/summary/',fil_list[j],'.Rdata'))
data_res_cancer <- data_res
weak_IV_data_2 <- subset(weak_IV_data,exposure %in% data_res_cancer$exposure)
weak_IV_data_2_formatted <- format_data(weak_IV_data_2,
type = "exposure",
phenotype_col = "exposure",
snp_col = "SNP",
beta_col = "beta.exposure",
se_col = "se.exposure",
eaf_col = "eaf.exposure",
effect_allele_col = "effect_allele.exposure",
other_allele_col = "other_allele.exposure",
pval_col = "pval.exposure",
samplesize_col = "samplesize.exposure",
gene_col = "gene",
id_col = "id.exposure",
chr_col = "chr.exposure",
pos_col = "pos.exposure")
outcome_data2 <- subset(outcome_data1,snp %in% weak_IV_data_2_formatted$SNP)
outcome_data2_formatted <- NULL
if(j<6){
outcome_data2_formatted <- format_data(outcome_data2,
type = "outcome",
phenotype_col = "cancer",
snp_col = "snp",
beta_col = "beta",
se_col = "se",
eaf_col = "EAF",
effect_allele_col = "ALT",
other_allele_col = "REF",
pval_col = "P",
chr_col = "CHROM",
pos_col = "POS")
} else{
outcome_data2_formatted <- format_data(outcome_data2,
type = "outcome",
phenotype_col = "cancer",
snp_col = "snp",
beta_col = "beta",
se_col = "se",
eaf_col = "EAF",
effect_allele_col = "ALT",
other_allele_col = "REF",
pval_col = "P")
}
dat <- harmonise_data(
exposure_dat = weak_IV_data_2_formatted,
outcome_dat = outcome_data2_formatted
)
results_wr <- mr(dat,method_list = "mr_wald_ratio")
# results_wr<-mr_singlesnp(dat)
if(nrow(results_wr)>0){
results_wr$outcome <- cancer_list[j]
write.csv(results_wr,paste("LHY/cancer_1/data/check/wr/",cancer_list[j],'_',"wr.txt",sep=""),row.names=FALSE)
}
cd4_data_check<-dat[which(duplicated(dat$id.exposure)),]
cd4_data_unique<-dat[-which(dat$id.exposure%in%cd4_data_check$id.exposure),]
if(nrow(cd4_data_unique)>0){
cd4_data_2plus<-dat[-which(dat$id.exposure%in%cd4_data_unique$id.exposure),]
} else{
cd4_data_2plus<-dat
}
results_wm<-mr(cd4_data_2plus,method_list = "mr_weighted_median")
results_wm$outcome <- cancer_list[j]
write.csv(results_wm,paste("cancer_1/data/check/wm/",cancer_list[j],'_',"wm.txt",sep=""),row.names=FALSE)
results_wm2<-mr(cd4_data_2plus,method_list = "mr_weighted_mode")
results_wm2$outcome <- cancer_list[j]
write.csv(results_wm2,paste("cancer_1/data/check/wm2/",cancer_list[j],'_',"wm2.txt",sep=""),row.names=FALSE)
exposure_names<-unique(cd4_data_2plus$exposure)
for (k in 1:length(exposure_names)){
cd4_data_2plus_use<-cd4_data_2plus[which(cd4_data_2plus$exposure==exposure_names[k]),]
f <- try(results_raps<-mr.raps.all(b_exp = cd4_data_2plus_use$beta.exposure,
b_out = cd4_data_2plus_use$beta.outcome,
se_exp = cd4_data_2plus_use$se.exposure,
se_out = cd4_data_2plus_use$se.outcome),silent = TRUE)
if(class(f)=='try-error'){
next
}
MR_RAPS_results<-cbind(exposure_names[k],nrow(cd4_data_2plus_use),
results_raps[1,1],results_raps[1,2],results_raps[1,3],results_raps[1,4])
write.table(MR_RAPS_results,
paste("cancer_1/data/check/RAPS/",cancer_list[j],'_',"RAPS.txt",sep=""),
col.names=FALSE,append=TRUE,row.names = FALSE,quote=FALSE)
}
for (l in 1:length(exposure_names)){
data_for_MR<-as.data.frame(cd4_data_2plus[which(cd4_data_2plus$exposure==exposure_names[l]),])
if(nrow(data_for_MR)>=4){
# Run MR-PRESSO global method
MR_PRESSO_results<-mr_presso(BetaOutcome = "beta.outcome",
BetaExposure = "beta.exposure",
SdOutcome = "se.outcome",
SdExposure = "se.exposure",
OUTLIERtest = TRUE,
DISTORTIONtest = TRUE,
data = data_for_MR,
NbDistribution = 1000,
SignifThreshold = 0.05)
MR_PRESSO_results<-cbind(exposure_names[l],nrow(data_for_MR),
MR_PRESSO_results$`Main MR results`[1,2],MR_PRESSO_results$`Main MR results`[1,3],MR_PRESSO_results$`Main MR results`[1,4],MR_PRESSO_results$`Main MR results`[1,6],
MR_PRESSO_results$`Main MR results`[2,2],MR_PRESSO_results$`Main MR results`[2,3],MR_PRESSO_results$`Main MR results`[2,4],MR_PRESSO_results$`Main MR results`[2,6])
write.table(MR_PRESSO_results,
paste("cancer_1/data/check/PRESSO/",cancer_list[j],'_',"PRESSO.txt",sep=""),
col.names=FALSE,append=TRUE,row.names = FALSE,quote=FALSE)
}
}
cd4_data_2plus$outcome<-cancer_list[j]
cd4_data_2plus_mr<-dat_to_MRInput(cd4_data_2plus)
for (k in 1:length(cd4_data_2plus_mr)){
data_for_MR<-cd4_data_2plus_mr[[k]]
f <- try(MR_CML<-mr_cML(data_for_MR,n=11900),silent = TRUE)
if(class(f)=='try-error'){
next
}
MR_CML_results<-cbind(names(cd4_data_2plus_mr[k]),MR_CML$SNPs,MR_CML$Estimate,MR_CML$StdError,MR_CML$CILower,MR_CML$CIUpper,MR_CML$Pvalue)
write.table(MR_CML_results,
paste("cancer_1/data/check/MR_CML/",cancer_list[j],'_',"MR_CML.txt",sep=""),
col.names=FALSE,append=TRUE,row.names = FALSE,quote=FALSE)
}
for (l in 1:length(cd4_data_2plus_mr)){
data_for_MR<-cd4_data_2plus_mr[[l]]
f <- try(MR_Robust<-mr_ivw(data_for_MR,robust = TRUE))
if(class(f)=='try-error'){
next
}
MR_Robust_results<-cbind(names(cd4_data_2plus_mr[l]),MR_Robust$SNPs,MR_Robust$Estimate,MR_Robust$StdError,MR_Robust$CILower,MR_Robust$CIUpper,MR_Robust$Pvalue)
write.table(MR_Robust_results,
paste("cancer_1/data/check/MRRobust/",cancer_list[j],'_',"MRRobust.txt",sep=""),
col.names=FALSE,append=TRUE,row.names = FALSE,quote=FALSE)
}
for (m in 1:length(cd4_data_2plus_mr)){
data_for_MR<-cd4_data_2plus_mr[[m]]
f <- try(MR_DIVW<-mr_divw(data_for_MR),silent = TRUE)
if(class(f)=='try-error'){
next
}
MR_DIVW_results<-cbind(names(cd4_data_2plus_mr[m]),MR_DIVW$SNPs,MR_DIVW$Estimate,MR_DIVW$StdError,MR_DIVW$CILower,MR_DIVW$CIUpper,MR_DIVW$Pvalue)
write.table(MR_DIVW_results,
paste("cancer_1/data/check/MRDIVW/",cancer_list[j],'_',"MRDIVW.txt",sep=""),
col.names=FALSE,append=TRUE,row.names = FALSE,quote=FALSE)
}
}