BMRV (version 1.32)

hbmr_ord: Hierarchical Bayesian multiple regression model incorporating genotype uncertainty (HBMR) for ordinal traits

Description

The function implements HBMR using a Gibbs sampler with probit link function for ordinal traits.

Usage

hbmr_ord(pheno, geno, qi = matrix(), fam = 0, kin = matrix(), iter = 10000, burnin = 500, 
gq = 20, imp = 0.1, cov = matrix(), maf = c(), pa = 1.3, pb = 0.04)

Arguments

pheno

A phenotypic vector ($N$ x 1). The trait must be a natural number (1, 2, 3, 4, ...).

geno

An $N$ x $K$ genotypic data matrix, where $N$ is the number of subjects and $K$ is the number of rare variants. Genotypic value is only for dominant coding, i.e. 0 or 1. Plug in 0 for imputed genotypes.

qi

An optional $N$ x $K$ Genotypic quality matrix, where $N$ is the number of subjects and $K$ is the number of rare variants. If the genotype is sequenced, this must be an integer >=1 and is its $GQ$ score in VCF file. If the genotype is imputed, this must be a value

fam

fam=1 for family samples. In this case, a relatedness matrix should be given. See kin.

kin

In the case of fam=1, kin is an $N$ x $N$ relatedness matrix. The scale of its entries are twice the kinship coefs, i.e. the same as that in coxme.

iter

The number of MCMC iterations. The default value is 10000.

burnin

The number of burn-ins. The default value is 500.

gq

A cutoff for $GQ$ score ($\lambda_Q$). It should be an positive integer. If not specified, default value is 20. See the reference for more details.

imp

A cutoff for imputed genotype ($\lambda_I$). It should be a real number in (0,1). If not specified, default value is 0.1. See the reference for more details.

cov

An optional $N$ x $M$ covariate data matrix, where $N$ is the number of subjects and $M$ is the number of covariates.

maf

An optional minor allele frequency information vector ($K$ by 1). If not specified, MAF will be estimated based on the genotype data.

pa

The positive hyper-parameter $a$ in the gamma distribution of Bayesian shrinkage prior. The default value is 1.3.

pb

The positive hyper-parameter $b$ in the gamma distribution of Bayesian shrinkage prior. The default value is 0.04.

Value

References

He, L., Pitkniemi, J., Sarin, A. P., Salomaa, V., Sillanp, M. J., & Ripatti, S. (2015). Hierarchical Bayesian Model for Rare Variant Association Analysis Integrating Genotype Uncertainty in Human Sequence Data. Genetic epidemiology, 39(2), 89-100.

Krkkinen, H. P., & Sillanp, M. J. (2013). Fast Genomic Predictions via Bayesian G-BLUP and Multilocus Models of Threshold Traits Including Censored Gaussian Data. G3: Genes| Genomes| Genetics, 3(9), 1511-1523.

Examples

data(hbmr_bin_data)
hbmr_ord(hbmr_bin_data$pheno[1:500], hbmr_bin_data$geno[1:500,1:3], fam=1, 
kin= hbmr_bin_data$kin[1:500,1:500], iter=800, burnin=200)