geneFilter: geneFilter

In simulatorZ: Simulator for Collections of Independent Genomic Data Sets

Description

the function to filter genes by Intergrative Correlation

Usage

geneFilter(obj, cor.cutoff = 0.5)

Arguments

obj	a list of ExpressionSet, matrix or RangedSummarizedExperiment objects. If its elements are matrices, columns represent samples, rows represent genes
cor.cutoff	the cutoff threshold for filtering genes. Only when the integrative correlation between every pair of sets is larger than the cutoff value, will the gene be selected.

Value

returns a list of ExpressionSets matrix or RangedSummarizedExperiment

objects with genes filtered

Author(s)

Yuqing Zhang, Christoph Bernau, Levi Waldron

References

Garrett-Mayer, E., Parmigiani, G., Zhong, X., Cope, L.,

Gabrielson, E., Cross-study validation and combined analysis of gene

expression microarray data. Biostatistics. 2008 Apr;9(2):333-354.

Examples

set.seed(8)


library(curatedOvarianData)


library(GenomicRanges)


data(GSE17260_eset)


data(E.MTAB.386_eset)


data(GSE14764_eset)


## to save time, we take a small subset from each dataset


esets.list <- list(GSE17260=GSE17260_eset[1:50, 1:10], 


                   E.MTAB.386=E.MTAB.386_eset[1:50, 1:10], 


                   GSE14764=GSE14764_eset[1:50, 1:10])


rm(E.MTAB.386_eset, GSE14764_eset, GSE17260_eset)





result.set <- geneFilter(esets.list, 0.1)


dim(result.set[[1]])





## as we cannot calculate correlation with one set, this function just 


## delivers the same set if esets has length 1


result.oneset <- geneFilter(esets.list[1])


dim(result.oneset[[1]])








## Support matrices


X.list <- lapply(esets.list, function(eset){


  return(exprs(eset)) ## Columns represent samples!


})


result.set <- geneFilter(X.list, 0.1)


dim(result.set[[1]])





## Support RangedSummarizedExperiment


nrows <- 200; ncols <- 6


counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)


rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)),


                     IRanges(floor(runif(200, 1e5, 1e6)), width=100),


                     strand=sample(c("+", "-"), 200, TRUE))


colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3),


                     row.names=LETTERS[1:6])


sset <- SummarizedExperiment(assays=SimpleList(counts=counts),


                             rowRanges=rowRanges, colData=colData)


s.list <- list(sset, sset)


result.set <- geneFilter(s.list, 0.9) 


## the same set should resemble each other, no genes filtered


dim(assay(result.set[[1]]))

simulatorZ documentation built on Nov. 8, 2020, 5 p.m.