ld_lasso_method: The LD LASSO function
In ldlasso: LD LASSO Regression for SNP Association Study

Description Usage Arguments Details Value Author(s) References See Also Examples

This function implements a method for the automatic selection of parameters for the LD LASSO. It returns three solutions, the fused, cp-optimal, and unfused solutions. It also creates a matrix of solutions needed for creating the trace plot.

1 2	ld_lasso_method(block.obj, block.cood = NA, Xa = NA, Y = NA, bpmap = NA, maxcol = 5e3, p.frac = 0.10, B = 5, s2low = 5e-3, s2high = 5e1, s2.vec.length = 4, null = FALSE)

`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.
`bpmap`	A vector of map positions in terms of kB from the left boundary
`maxcol`	The upper limit on the number of columns in the constraint matrix. This is to prevent computational overload. Increasing maxcol may increase computation time and memory needed.
`p.frac`	The fraction of SNPs allowed in LASSO model under null hypothesis. This parameter is used in the function get.s1.
`B`	The number of bootstrap iterations for cp estimate.
`s2low`	The lower limit of the s2 vector
`s2high`	The upper limit of the s2 vector
`s2.vec.length`	The number of exponentially spaced values of s2.
`null`	A logical variable that indicates if analysis should be performed on permuted phenotype vector.

Use function find.bounds to create block.cood vector with MATILDE MCMC methods. See ldlasso help page for details on the package MATILDE.

`beta1`	The ld lasso solution with s2 that minimizes cp (cp-optimal solution)
`beta2`	The ld lasso solution for lower limit of s2 interval (fused solution)
`beta3`	The ld lasso solution for upper limit of s2 interval (unfused solution)
`s2star`	The s2 value that minimizes cp
`cp.obj`	A list that contains information used for cp estimation
`log10p`	A vector of log10 p values for test of allelic association
`bpmap`	A vector of map positions in base pairs
`block.bounds.vec`	A vector of block boundaries in kB from left boundary
`s1`	the LASSO constraint
`B`	Number of bootstrap samples
`s2.vec.length`	The length of the s2 vector

Samuel G. Younkin

Samuel Younkin, Joseph Nadeau, Robert Elston and J. Sunil Rao, "The Linkage Disequilibrium LASSO for SNP Selection in a Genetic Association Study of Late Onset Alzheimer Disease," Technical Report, 2010

ld_lasso

  # Load example data
  # data(ldlasso_example)
  
  # Run the method with low B and s2.vec.length first to test.
  # ldlasso.obj <- ld_lasso_method( block.obj, block.cood, B = 3, s2.vec.length = 2 )

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