#' Function "ensemblTOentrez"
#'
#' This function can be called without DESeq, input a gene expression matrix based on ensembl IDs
#' and output the corresponding matrix based on entrez IDs
#' @importFrom plyr join
#' @param geneExp a data object with ensembl IDs as rownames
#' @param geneSymbol a data frame with all gene annotation information
#' @param condition character vector containing group condition
#' @param n1 the number of one condition in "condition"
#' @param n2 the numbe of the second condition in "condition"
#' @return an ExpressionSet object with matrix based on entrez gene IDs
#' @export
ensemblTOentrez <- function(geneExp, geneSymbol, condition, n1, n2) {
geneExpI <- as.data.frame(geneExp)
geneExpI$ensembl_gene_id <- row.names(geneExp)
geneExpI <- join(geneExpI, geneSymbol[, c("entrezgene_id", "ensembl_gene_id")], by="ensembl_gene_id")
geneExpI <- aggregate(geneExpI[, 1:ncol(geneExp)], by=list(entrez=geneExpI$entrezgene_id), FUN=mean)
row.names(geneExpI) <- as.character(geneExpI$entrez)
geneExpI <- as.matrix(geneExpI)[, -1]
# create phenotype file
meta.phe <- data.frame(SampleID = colnames(geneExpI),
Group = factor(c(rep(condition[1], n1), rep(condition[2], n2))),
row.names = colnames(geneExpI))
meta_phe <- data.frame(labelDescription=c('SampleID', 'Group'),
row.names=c('SampleID', 'Group'))
gene.phe <- new("AnnotatedDataFrame", data=meta.phe, varMetadata=meta_phe)
# construct ExpressionSet object from gene.exp and gene.phe
gene.es <- ExpressionSet(assayData=geneExpI,
phenoData=gene.phe,
annotation="hgu95av2")
# return result
return(gene.es)
}
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