r2.cut.fn: Find the r-squared cutoff

In ldlasso: LD LASSO Regression for SNP Association Study

Description

Returns the minimum value of r2 in r2.vec that keeps the number of constraint matrix columns less than maxcol.

Usage

r2.cut.fn(block.obj, block.cood, Xa, Y, maxcol, r2.cut.min, r2.cut.max, r2.vec.length)

Arguments

block.obj	An object of class gwaa.data from GenABEL.
block.cood	A vector of length p+1, where p is the number of SNPs. block.cood is an indicator vector that indicates block boundaries at all p+1 SNP bounded intervals. Use find.bounds to create this vector.
Xa	If block.obj is NA then a genotype matrix must be provided. Xa is a matrix of genotype values codes as 0, 1 or 2 for homozygous major, heterozygous, or homozygous minor, respectively.
Y	If block.obj is NA then a phenotype vector Y must be provided. Y is a vector of diagnoses, where 0 is non-diseased and 1 is diseased.
maxcol	The maximum number of columns allowed in the constraint matrix. Default is 5,000.
r2.cut.min	The lower bound of the r2.cut interval
r2.cut.max	The upper bound of the r2.cut interval
r2.vec.length	The number of r2.cut values uniformly spaced in r2.cut interval

Value

The function r2.cut.fn returns the minimum value of r2.cut that satsisfies, ncol(A) < maxcol, where A is the constraint matrix

Author(s)

Samuel G. Younkin

See Also

ld_lasso

ldlasso documentation built on May 30, 2017, 3:05 a.m.