covmat: Estimate covariance matrices

In gqi/hipo: Heritability Informed Power Optimization (HIPO)

Description

Uses LD score regression to estimate the genetic covariance matrix and LDSC intercept matrix, which are needed for HIPO analysis.

Usage

covmat(sumstats.all, traitvec, out.path, ldsc.path, python.path = NULL,
  ldscore.path = file.path(ldsc.path, "eur_w_ld_chr/"), mergeallele = TRUE)

Arguments

sumstats.all	Summary statitics of all individual traits, first output of preprocess().
traitvec	Vector of trait names, second output of preprocess().
out.path	The path where the LDSC intermediate outputs are stored.
ldsc.path	The path of the LDSC software.
python.path	The path of Python, if you need to use a version other than the default one.
ldscore.path	The path containing the LDSC LD score files. Default to be file.path(ldsc.path,"eur_w_ld_chr/").
mergeallele	Corresponds to the --merge-allele flag in LDSC, indicates whether to merge alleles to HapMap 3 SNPs. Default to be TRUE.

Value

A list containing

coherit.mat	Genetic covariance matrix.
ldscint.mat	LD score regression intercept matrix.

gqi/hipo documentation built on May 18, 2019, 8:12 p.m.