RFGLS-package: Rapid Feasible Generalized Least Squares
In RFGLS: Rapid Feasible Generalized Least Squares

Description Details Author(s) References

RFGLS uses a generalized least-squares method to perform single-marker association analysis, in datasets of nuclear families containing parents, twins, and/or adoptees. It is designed for families of no greater than four members. When conducting association analysis with a large number of markers, as in GWAS, RFGLS uses rapid feasible generalized least-squares, an approximation to feasible generalized least-squares (FGLS) that considerably reduces computation time with minimal bias in p-values, and with negligible loss in power.

The package includes four functions. Function gls.batch() actually conducts GWAS using the rapid feasible generalized least-squares approximation, under which the residual variance-covariance matrix is estimated once from a regression of the phenotype onto covariates only, and is subsequently "plugged in" for use in all subsequent single-SNP analyses. Function fgls() is called by gls.batch(), and conducts a single FGLS regression. It can be used to simultaneously estimate fixed-effects regression coefficients and the residual covariance matrix. Function gls.batch.get() is useful to restructure data, for use with fgls(). Function FSV.frompedi() creates family-structure variables based upon available information in a pedigree file. Functions gls.batch() and gls.batch.get() use these family-structure variables, which represent the type of family to which each participant belongs and how s/he fits into that family.

Package:	RFGLS
Version:	1.1
Date:	2013/8/29
Depends:	R (>= 2.15.0), stats, bdsmatrix, Matrix
License:	GPL (>= 2)

Robert M. Kirkpatrick rkirkpatrick2@vcu.edu, Xiang Li lixxx554@umn.edu, and Saonli Basu saonli@umn.edu .

Maintainer: Saonli Basu <saonli@umn.edu>

Li X, Basu S, Miller MB, Iacono WG, McGue M: A Rapid Generalized Least Squares Model for a Genome-Wide Quantitative Trait Association Analysis in Families. Human Heredity 2011;71:67-82 (DOI: 10.1159/000324839)

RFGLS documentation built on May 2, 2019, 2:51 p.m.