hibayes (version 3.0.3)

ldmat: LD variance-covariance matrix calculation

Description

To calculate density or sparse LD variance-covariance matrix with genotype in bigmemory format.

Usage

ldmat(
  geno,
  map = NULL,
  gwas.geno = NULL,
  gwas.map = NULL,
  chisq = NULL,
  ldchr = FALSE,
  threads = 4,
  verbose = FALSE
)

Value

For full ld matrix, it returns a standard R matrix, for sparse matrix, it returns a 'dgCMatrix'.

Arguments

geno

the reference genotype panel in bigmemory format.

map

the map information of reference genotype panel, columns are: SNPs, chromosome, physical position.

gwas.geno

(optional) the genotype of gwas samples which were used to generate the summary data.

gwas.map

(optional) the map information of the genotype of gwas samples, columns are: SNPs, chromosome, physical position.

chisq

chi-squre value for generating sparse matrix, if n*r2 < chisq, it would be set to zero.

ldchr

lpgical, whether to calulate the LD between chromosomes.

threads

the number of threads used in computation.

verbose

whether to print the information.

Examples

bfile_path = system.file("extdata", "demo", package = "hibayes")
data = read_plink(bfile_path)
geno = data$geno
map = data$map
# \donttest{
xx = ldmat(geno, threads=4, verbose=FALSE)   #chromosome wide full ld matrix
# xx = ldmat(geno, chisq=5, threads=4)   #chromosome wide sparse ld matrix
# xx = ldmat(geno, map, ldchr=FALSE, threads=4)   #chromosome block ld matrix
# xx = ldmat(geno, map, ldchr=FALSE, chisq=5, threads=4)   #chromosome block + sparse ld matrix
# }