gap (version 1.5-1)

b2r: Obtain correlation coefficients and their variance-covariances

Description

This function converts linear regression coefficients of phenotype on single nucleotide polymorphisms (SNPs) into Pearson correlation coefficients with their variance-covariance matrix. It is useful as a preliminary step for meta-analyze SNP-trait associations at a given region. Between-SNP correlations (e.g., from HapMap) are required as auxiliary information.

Usage

b2r(b, s, rho, n)

Value

The returned value is a list containing:

r

the vector of correlation coefficients

V

the variance-covariance matrix of correlations

Arguments

b

the vector of linear regression coefficients.

s

the corresponding vector of standard errors.

rho

triangular array of between-SNP correlation.

n

the sample size.

Author

Jing Hua Zhao

References

Becker BJ (2004). Multivariate meta-analysis. in Tinsley HEA, Brown SD (Ed.) Handbook of Applied Multivariate Statistics and Mathematical Modeling (Chapter 17, pp499-525). Academic Press.

Casella G, Berger RL (2002). Statistical Inference, 2nd Edition, Duxbury.

Elston RC (1975). On the correlation between correlations. Biometrika 62:133-40

See Also

mvmeta, LD22

Examples

if (FALSE) {
n <- 10
r <- c(1,0.2,1,0.4,0.5,1)
b <- c(0.1,0.2,0.3)
s <- c(0.4,0.3,0.2)
bs <- b2r(b,s,r,n)
}