% 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"))

}