GLA-methods {LiquidAssociation} | R Documentation |
'GLA' is used to calculate the GLA estimate for a gene triplet data.
object |
An numerical matrix object with three columns or an object of ExpresionSet class with three features. |
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). |
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.
'GLA' returns a numerical value representing the estimated value. A more detailed interpretation of the value is illustrated in the vignette.
Yen-Yi Ho
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
data<-matrix(rnorm(300), ncol=3) colnames(data)<-c("Gene1", "Gene2", "Gene3") GLAest<-GLA(data, cut=4, dim=3) GLAest