asym_m_ng {NGBVS}

Modified NG prior via FS scores

Description

Modified Normal Gamma prior calculates the posterior distribution for the fine mapping cases-controls study. The number of case-controls must be greater than the number of SNPs.

Usage

asym_m_ng (y, data, FS, medstar = c(0.01, 0.0001), numb = 100, burnin = 1, every = 1)

Arguments

y

A vector of the pheontype, where takes 0s and 1s.

data

An N \times p finemap data, where N and p denote the samples and number of SNPs respectively.

FS

FS scores for each SNP and it takes value from 0 and 1 or NA for missing FS.

medstar

The value of M where M takes two values.

numb

Number of samples for each SNP.

burnin

The amount of burn-in for the MCMC sample.

every

The amount of thining for the MCMC sample.

Value

A list including:

alpha

A vector of the posterior distribution of the intercept.

beta

A matrix of the posterior distribution of the effect sizes.

psi

A matrix of the posterior distribution of \psi.

lambda

A vector of the posterior distribution of \lambda.

gammasq

A vector of the posterior distribution of \gamma^2.

W

A vector of the posterior distribution of W.

H

A vector of the posterior distribution of H.

Author(s)

Abulaziz Alenazi.

R implementation and documentation: Abulaziz Alenazi [e-mail].

Examples

set.seed(1)
data <- matrix(sample( c( 0, 1, 2 ), 500 * 30, replace = TRUE,
prob <- c( 0.35, 0.35, 0.3)), ncol = 30 )
FS <- sample( c( 0.1, 0.5, 0.7, NA ), ncol( data ), replace = TRUE)
asym_m_ng(y = rbinom(500, 1, 0.5), data = data, FS = FS)