Each of these raw files were generated from plink (see https://ucsdhs-my.sharepoint.com/:p:/g/personal/cil001_health_ucsd_edu/EQqeRJc5m5NNtl7B-SMwN3UBxxeoSBHCjBMnjLWFfoxKUA?e=xIEBVo for powerpoint expalination).

But basically these are genetics data. The FID is Family ID, IID is individual ID. So each row is a person.

The PAT, MAT, SEX, PHENOTYPE columns are other info taken about the person in this particular case we don't really worry about them in this project so just igore them for now.

Now see the column 'X1.1733219.A.G_A' and all the columns after it all look something similar to it. These are actual data of that person's DNA, SNP data.

• Let me break it down, here's how to read 'X1.1733219.A.G_A'

• "X1" expalin we are in chromosome 1

• "1733219" is the base pair position. You can think of this, the exact location of where within the chromosome.

  • So we know we are in chromosome 1, but where within chromosome 1? This is what the base pair position explains, we are at location 1733219 within chromosome 1.

We would like to take all the SNPs from the 4 list and input them into LDproxy. We want to comobine the LDproxy into 4 big lists in the end so we can have all the LDproxy SNP names in one .txt file

That file has been generated with a R2 > 0.8 cut off : /space/chen-syn01/1/data/cinliu/data/clozapine/data_April2021/LD_proxy/R08

That is the end goal of this project, 4 simple .txt files with SNP ID fetched from LDproxy - the SNPs we input into LDproxy will be from 4 files:

• /space/chen-syn01/1/data/cinliu/data/clozapine/data_April2021/All_CLZ_samples_snplist1_a1updated.raw

• /space/chen-syn01/1/data/cinliu/data/clozapine/data_April2021/All_CLZ_samples_snplist2_a1updated.raw

• /space/chen-syn01/1/data/cinliu/data/clozapine/data_April2021/All_TOP_samples_snplist1_updated.raw

• /space/chen-syn01/1/data/cinliu/data/clozapine/data_April2021/All_TOP_samples_snplist2_updated.raw

Summary of what's happening right now

You can merge the files after removing the SNPs with R2 <0.2 and we 'll see the total number.

3_remove_duplicated.R

rm(list=ls())

savedir = "/Users/nini/Desktop/2021lab/CH/LDproxy_fetch/" #UPDATE location of save loaction

clz1 <- "~/Desktop/2021lab/CH/LDproxy_fetch/All_CLZ_samples_snplist1_a1updated_LDproxy/clzsnplist1_all_server_and_local.tsv"

clz2 <- "/Users/nini/Desktop/2021lab/CH/LDproxy_fetch/All_CLZ_samples_snplist2_a1updated_LDproxy_FULL_List.tsv"

top1 <- "~/Desktop/2021lab/CH/LDproxy_fetch/All_TOP_samples_snplist1_LDproxy/topsnplist1_all_server_and_local.tsv"

top2 <- "/Users/nini/Desktop/2021lab/CH/LDproxy_fetch/All_TOP_samples_snplist2_LDproxy_FULL_List.tsv"

df_name <- c("All_CLZ_samples_snplist1_a1updated","All_CLZ_samples_snplist2_a1updated","All_TOP_samples_snplist1","All_TOP_samples_snplist2")

df_list <- c(clz1,clz2,top1,top2)

for (i in 1:4) {

df <- read.delim(df_list[i])

print(df_list[i])

df2 <- df[df$R2 >0.5,] #only keep those that have R >0.5

nodouble <- df2[!duplicated(df2$RS_Number), ] #remove duplicated RS_number

nodouble <- nodouble[!nodouble$R2 == "R2",] #remove the row that is column names

#print(nrow(nodouble))

nodouble <- nodouble[!duplicated(nodouble$Coord), ] #remove duplicated RS

nodouble$Coord <- gsub("chr", "", nodouble$Coord) #change to CHR:POS from

nodouble <- nodouble[c(2,1,3,4,5,6,7,8,9,10)] #reorder so CHR:POS is the first column

write.table(nodouble,file = paste0(savedir,df_name[i],"_LDproxy_r05.tsv"),row.name = F, col.names = T, quote = F,sep='\t')

#print(nrow(nodouble))

df3 <- nodouble[,c(1)] #only selecting the CHR:POS

write.table(df3,file = paste0(savedir,df_name[i],"_LDproxy_r05_SNPID_list.txt"),quote = FALSE,row.names = FALSE, col.names = "CHR:POS")

#print(length(df3))

}