% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/shaPRS.R
\name{LDRefBlend}
\alias{LDRefBlend}
\title{Generate shaPRS specific LD reference panel}
\usage{
LDRefBlend(pop1LDmatrix, pop2LDmatrix, sumstatsData, memoryEfficiency = 5)
}
\arguments{
\item{pop1LDmatrix}{LD reference matrix in RDS (dsCMatrix) format for target population}

\item{pop2LDmatrix}{LD reference matrix in RDS (dsCMatrix) format for other population}

\item{sumstatsData}{summary data with required columns of SE_A, SE_B, A1.x, A1.y, and lFDR}

\item{memoryEfficiency}{larger numbers result in longer runs but lower memory usage (default 5)}
}
\value{
returns a PRS specific LD matrix
}
\description{
Generates a PRS specific LD reference matrix by blending together two LD ref panels according to
shaPRS produced lFDR and standard errors
}
\examples{
sumstatsData = readRDS(file = system.file("extdata", "sumstatsData_toy.rds", package = "shaPRS") )

# read SNP map files (same toy data for the example)
pop1_map_rds = readRDS(file = system.file("extdata", "my_data.rds", package = "shaPRS") )
pop2_map_rds = readRDS(file = system.file("extdata", "my_data2.rds", package = "shaPRS") )

# use chrom 21 as an example
chromNum=21

# load the two chromosomes from each population ( same toy data for the example)
pop1LDmatrix = readRDS(file = system.file("extdata", "LDref.rds", package = "shaPRS") )
pop2LDmatrix = readRDS(file = system.file("extdata", "LDref2.rds", package = "shaPRS") )


# 2. grab the RSids from the map for the SNPS on this chrom,
# each LD mat has a potentially different subset of SNPs
# this is guaranteed to be the same order as the pop1LDmatrix
pop1_chrom_SNPs = pop1_map_rds[ which(pop1_map_rds$chr == chromNum),]
# this is guaranteed to be the same order as the pop2LDmatrix
pop2_chrom_SNPs = pop2_map_rds[ which(pop2_map_rds$chr == chromNum),]
pop1_chrom_SNPs$pop1_id = 1:nrow(pop1_chrom_SNPs)
pop2_chrom_SNPs$pop2_id = 1:nrow(pop2_chrom_SNPs)


# intersect the 2 SNP lists so that we only use the ones common to both LD matrices by merging them
chrom_SNPs_df  <- merge(pop1_chrom_SNPs,pop2_chrom_SNPs, by = "rsid")

# align the two LD matrices
chrom_SNPs_df = alignStrands(chrom_SNPs_df, A1.x ="a1.x", A2.x ="a0.x", A1.y ="a1.y", A2.y ="a0.y")


# align the summary for phe A and B
sumstatsData = alignStrands(sumstatsData)

# subset sumstats data to the same chrom
sumstatsData = sumstatsData[which(sumstatsData$CHR == chromNum ),]

# merge sumstats with common LD map data
sumstatsData  <- merge(chrom_SNPs_df,sumstatsData, by.x="rsid", by.y = "SNP")

# remove duplicates
sumstatsData = sumstatsData[ !duplicated(sumstatsData$rsid) ,]
# use the effect alleles for the sumstats data with the effect allele of the LD mat
# as we are aligning the LD mats against each other, not against the summary stats
# we only use the lFDR /SE from the sumstats,
# which are directionless, so those dont need to be aligned
sumstatsData$A1.x =sumstatsData$a1.x
sumstatsData$A1.y =sumstatsData$a1.y

# make sure the sumstats is ordered the same way as the LD matrix:
sumstatsData = sumstatsData[order(sumstatsData$pop1_id), ]
# it doesn't matter which matrix to use to order the sumstats as they are the same

# subset the LD matrices to the SNPs we actually have
pop1LDmatrix = pop1LDmatrix[sumstatsData$pop1_id,sumstatsData$pop1_id]
pop2LDmatrix = pop2LDmatrix[sumstatsData$pop2_id,sumstatsData$pop2_id]

# generate the blended LD matrix
cormat = LDRefBlend(pop1LDmatrix,pop2LDmatrix, sumstatsData)

# create a new map file that matches the SNPs common to both LD panels
map_rds_new = pop1_map_rds[which(pop1_map_rds$chr == chromNum),]
map_rds_new2 = map_rds_new[which(map_rds_new$rsid \%in\% sumstatsData$rsid),]

# save the new LD matrix to a location of your choice
# saveRDS(cormat,file =paste0(<YOUR LOCATION>,"/LD_chr",chromNum,".rds"))

# save its Map file too
# saveRDS(map_rds_new2,file = paste0(<YOUR LOCATION>,"/LD_chr",chromNum,"_map.rds"))

}