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R: a way to control a microarray data matrix when rows and columns have additional annotation tables

Data

I often work with data like microarray. It has a number matrix and annotations for columns and rows. You can think of columns as faces, of rows as genes and matrices as some measure for each gene-individual pair. Here is a smaller simulated version: (real data can have millions of rows).

p <- 500000
N <- 50
mat <- matrix(rnorm(p*N), ncol=N)
colData <- replicate(10, sample(letters[sample(26, 4)], N, replace=TRUE))
colnames(colData) <- toupper(letters[1:10])
rowData <- data.frame("chromosome"=rep(c("chr1","chr2"), rep(p/2,2)),
                      "coordinates"=rep(1:(p/2), 2),
                      "someScore"=round(runif(p, max=10))
                     )

Thus, each row in rowInfo has an annotation for the gene and each column in colInfo - an annotation for an individual (I think: gender, age, etc.).

My user approach is to combine all the information into one list:

theData <- list(mat=mat, rowInfo=rowData, colInfo=colData)
rm(mat, rowData, colData)

And use custom functions to manage this data.

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