getsGLA-methods: Function to calculate the sGLA test statistic for a given triplet data

Description

'getsGLA' is used to calculate the sGLA test statistic and correponding p value.

Arguments

object

An numerical matrix object with three columns or an object of ExpresionSet class with three features.

boots

The number of bootstrap iterations for estimating the bootstrap standard error of sGLA. Default value is boots=30.

perm

The number of permutation iterations for generating the null distribution of the sGLA test statistic. Default is perm=100.

cut

cut==M +1. M is the number of grip points pre-specifed over the third variable.

dim

An index of the column for the gene to be treated as the third controller variable. Default is dim=3

geneMap

A character vector with three elements representing the mapping between gene names and feature names (optional).

Value

'getsGLA' returns a vector with two elements. The first element is the value of test statistic and second element is the corresponding p value. A more detailed interpretation of these values is illustrated in the vignette.

Details

The input object can be a numerical matrix with three columns with row representing observations and column representing three variables. It can also be an ExpressionSet object with three features. If input a matrix class data, all three columns of the object representing the variables should have column names. Each variable in the object will be standardized with mean 0 and variance 1 in the function. In addition, the third variable will be quantile normalized within the function. More detail example about the usage of geneMap is demonstrated in the vignette.

References

Yen-Yi Ho, Leslie Cope, Thomas A. Louis, and Giovanni Parmigiani, GENERALIZED LIQUID ASSOCIATION (April 2009). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 183. http://www.bepress.com/jhubiostat/paper183.

Examples

Run this code

data<-matrix(rnorm(300), ncol=3)

colnames(data)<-c("Gene1", "Gene2", "Gene3")

sGLAest<-getsGLA(data, boots=20, perm=100, cut=4, dim=3)

sGLAest