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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)

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

Value

The returned value is a list containing:

`r`	the vector of correlation coefficients
`V`	the variance-covariance matrix of correlations

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

Author(s)

Jing Hua Zhao

Examples

## Not run: 
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)

## End(Not run)

gap

Genetic Analysis Package

v1.2.3-1

GPL (>= 2)

Authors

Jing Hua Zhao and colleagues with inputs from Kurt Hornik and Brian Ripley

Initial release

2021-4-21

b2r