Attractor: Class '"Attractor"'

In weiyi-bitw/cafr: Attractor Metagenes Finding Algorithm

Description

A reference class for an attractor object. This object is used to summarize attractors found in difference datasets. And also a basic building block for class AttractorSet. It contains top genes in an attractor, and a method getOverlapNum to return the number of overlapping genes with other attractors.

Extends

All reference classes extend and inherit methods from "envRefClass".

Fields

id:

ID of the Attractor.

genes:

A vector of top genes and their MIs in the attractor.

strength:

The strength of the attractor, defined by the qt-th highest MI in the attractor as assigned when initialized.

src:

The source of the attractor, usually the name of the dataset from which the attractor is generated.

Methods

getOverlapNum(a):

Returns the number of overlapping genes with another Attractor or AttractorSet object.

Arguments:

a : An object of Attractor or Attractor Set.

initialize(id, a, genenames, src, numgenes, qt):

Initialize an Attractor object

Arguments:

id : ID of the attractor

a : A vector of MIs of the genes in the attractor. As output by the findAttractor function

genenames : A vector of all gene symboles in the dataset.

src : The source of the attractor, usually the name of the dataset it is generated.

numgenes : Number of top genes stored in the object.

qt : Which rank should be used to represent the strength of the attractor. Default is the 10th highest MI

Author(s)

Wei-Yi Cheng

References

Wei-Yi Cheng, Tai-Hsien Ou Yang and Dimitris Anastassiou, Biomolecular events in cancer revealed by attractor metagenes, PLoS Computational Biology, Vol. 9, Issue 2, February 2013.

See Also

AttractorSet, findAttractor

Examples

showClass("Attractor")

## ======== Find the CIN attractor in the ov dataset =======
# Load the toy dataset extracted from TCGA OV data
data(ov)

# find attractor using CENPA as a seed
x <- ov["CENPA",]
a <- findAttractor(ov, x)

attractor1 <- Attractor$new("OV001", a, genenames=names(a), src="OV", numgenes=100, qt=10)

## ======== Find the CIN attractor in the brca.pbs dataset======
# load Toy version of Wang et al. breast cancer dataset (GSE2034)
data(brca.pbs)

# download the HGU133A 2.0 annotations
source("http://bioconductor.org/biocLite.R")
biocLite("hgu133a2.db")
library(hgu133a2.db)

# Create map object to fit the format
x <- hgu133a2SYMBOL
map <- cbind(unlist(as.list(x[mappedkeys(x)])))
colnames(map) <- "Gene.Symbol"

# summarize into gene-level expression after eliminating uncorrelated probes
brca <- probeSummarization(brca.pbs, map)

x <- brca["CENPA",]
a <- findAttractor(brca, x)

attractor2 <- Attractor$new("BRCA001", a, genenames=names(a), src="BRCA", numgenes=100, qt=10)

# Find the number of overlapping genes between the two attractors
attractor1$getOverlapNum(attractor2)

# Initialize an AttractorSet object using the OV CIN attractor
attractorSet1 <- AttractorSet$new(id="AttractorSet001", a=attractor1, k=2)
# add the BRCA CIN attractor
attractorSet1$add(attractor2)
# rank the genes in the attractor set according to their occurrence
head(attractorSet1$getGeneTable())
# create a consensus attractor using the two CIN attractors
attractorSet1$getConsensus()
# shows the matrix of top genes in each attractor in the attractor set
attractorSet1$getGeneMatrix()

weiyi-bitw/cafr documentation built on May 4, 2019, 4:18 a.m.