% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/shaPRS.R

\name{shaPRS}

\alias{shaPRS}

\title{Creates a new set of summary statistics}

\usage{

shaPRS(

  proximalLoc,

  adjunctLoc,

  outputLoc,

  rho = 0,

  discardAmbiguousSNPs = T,

  useProximalForMissing = T

)

}

\arguments{

\item{proximalLoc}{proximal LDPred formatted GWAS summary statistics table  that has header with the following columns: chr    pos    SNP    A1    A2    Freq1.Hapmap    b    se    p    N}

\item{adjunctLoc}{dataframe for adjunct dataset of the same signature}

\item{outputLoc}{the location of the output files}

\item{rho}{estimate of correlation between studies due to shared subjects. 0 for no overlap and 1 for complete overlap. default: 0. Obtain this from shaPRS_rho()}

\item{discardAmbiguousSNPs}{(optional) if ambiguous SNPs (G/C and A/T) should be discarded (default TRUE)}

\item{useProximalForMissing}{(optional) if SNPs missing from the adjunct data should be kept using the proximal data or not (default TRUE)}

}

\description{

it performs both steps of the shaPRS method in a single call:

(1) Creates lFDR corrected Q-test statistics for each SNP (via shaPRS_adjust)

(2) produce summary statistics according to a continuous weighting scheme (via shaPRS_blend_overlap)

(3) It writes to disk the following files with postfixes:   "_adjustinput", "_SNP_lFDR", "_shaprs", "_meta", which are the input and output for shaPRS_adjust (also required for shaPRS_LDGen), and shaPRS adjusted summary stats and a fixed-effect meta-analysis

}

\examples{

proximalLoc <- system.file("extdata", "phenoA_sumstats", package = "shaPRS")

adjunctLoc <- system.file("extdata", "phenoB_sumstats", package = "shaPRS")

shaPRS(proximalLoc, adjunctLoc, tempfile())

}