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R: Between-groups sum-of-squares to within-groups sum-of-squares...

BssWssFast

R Documentation

Between-groups sum-of-squares to within-groups sum-of-squares ratio

Description

This is a univariate technique to select relevant genes in classification of microarray data. In classifying samples of microarray data, this ratio is computed for each gene. A large between-groups to within-groups sum-of-squares ratio indicates a potentially relevant gene.

Usage

BssWssFast (X, givenClassArr, numClass = 2)

Arguments

`X`	data matrix where columns are variables and rows are observations. In the case of gene expression data, the columns (variables) represent genes, while the rows (observations) represent samples or experiments.
`givenClassArr`	class vector for the observations (samples or experiments). Class numbers are assumed to start from 0, and the length of this class vector should be equal to the number of rows in X. In the case of 2-class data, we expect the class vector consists of zero's and one's.
`numClass`	number of classes. The default is 2.

Details

This function is called by iterateBMAglm.2class.

Value

A list of 2 elements are returned:

`x`	A vector containing the BSS/WSS ratios in descending order.
`ix`	A vector containing the indices corresponding to the sorted ratios.

References

Dudoit, S., Fridlyand, J. and Speed, T.P. (2002) Comparison of discrimination methods for the classification of tumors using gene expression data. Journal of the American Statistical Association 97: 77-87.

Yeung, K.Y., Bumgarner, R.E. and Raftery, A.E. (2005) Bayesian Model Averaging: Development of an improved multi-class, gene selection and classification tool for microarray data. Bioinformatics 21: 2394-2402.

Examples

data(trainData)
data(trainClass)

ret.bsswss <- BssWssFast (X=t(exprs(trainData)), givenClassArr=trainClass, numClass = 2)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(iterativeBMA)
Loading required package: BMA
Loading required package: survival
Loading required package: leaps
Loading required package: robustbase

Attaching package: 'robustbase'

The following object is masked from 'package:survival':

    heart

Loading required package: inline
Loading required package: rrcov
Scalable Robust Estimators with High Breakdown Point (version 1.3-11)

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")'.


Attaching package: 'Biobase'

The following object is masked from 'package:robustbase':

    rowMedians

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/iterativeBMA/BssWssFast.Rd_%03d_medium.png", width=480, height=480)
> ### Name: BssWssFast
> ### Title: Between-groups sum-of-squares to within-groups sum-of-squares
> ###   ratio
> ### Aliases: BssWssFast
> ### Keywords: univar
> 
> ### ** Examples
> 
> data(trainData)
> data(trainClass)
> 
> ret.bsswss <- BssWssFast (X=t(exprs(trainData)), givenClassArr=trainClass, numClass = 2)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>