Function to calculate GLA estimate

Description

'GLA' is used to calculate the GLA estimate for a gene triplet data.

Arguments

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.

Value

'GLA' returns a numerical value representing the estimated value. A more detailed interpretation of the value is illustrated in the vignette.

Author(s)

Yen-Yi Ho

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

See Also

LA-methods, getsGLA-methods

Examples

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

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

GLAest<-GLA(data, cut=4, dim=3)

GLAest

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(LiquidAssociation)
Loading required package: geepack
Loading required package: yeastCC
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: org.Sc.sgd.db
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums


> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/LiquidAssociation/GLA-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: GLA-methods
> ### Title: Function to calculate GLA estimate
> ### Aliases: GLA-methods GLA,eSet-method GLA,matrix-method GLA
> ### Keywords: methods
> 
> ### ** Examples
> 
> 
> data<-matrix(rnorm(300), ncol=3)
> 
> colnames(data)<-c("Gene1", "Gene2", "Gene3")
> 
> GLAest<-GLA(data, cut=4, dim=3)
> 
> GLAest
GLA(Gene1,Gene2|Gene3) 
           -0.05445531 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>