[R] Cube of Matrices or list of Matrices

[Karim Mezhoud]

Yes Many thanks.
That is my request using lapply.

do.call(cbind,col1)

 converts col1 to matrix but does not fill empty value with NA.

Even for

matrix(unlist(col1), ncol=5,byrow = FALSE)


How can get Matrix class of col1? And fill empty values with NA?

Thanks
Karim


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On Mon, Jan 19, 2015 at 4:36 PM, Ben Tupper <ben.bighair at gmail.com> wrote:

> Hi,
>
> On Jan 18, 2015, at 4:36 PM, Karim Mezhoud <kmezhoud at gmail.com> wrote:
>
> > Dear All,
> > I am trying to get correlation between  Diseases (80) in columns and
> > samples in rows (UNEQUAL) using gene expression (at less 1000,numeric).
> For
> > this I can use CORREP package with cor.unbalanced function.
> >
> > But before to get this final matrix I need to load and to store the
> > expression of 1000 genes for every Disease (80). Every disease has
> > different number of samples (between 50 - 500).
> >
> > It is possible to get a cube of matrices with equal columns but unequal
> > rows? I think NO and I can't use array function.
> >
> > I am trying to get à list of matrices having the same number of columns
> but
> > different number of rows. as
> >
> > Cubist <- vector("list", 1)
> > Cubist$Expression <- vector("list", 1)
> >
> >
> > for (i in 1:80){
> >
> > matrix <- function(getGeneExpression[i])
> > Cubist$Expression[[Disease[i]]] <- matrix
> >
> > }
> >
> > At this step I have:
> > length(Cubist$Expression)
> > #80
> > dim(Cubist$Expression$Disease1)
> > #526 1000
> > dim(Cubist$Expression$Disease2)
> > #106  1000
> >
> > names(Cubist$Expression$Disease1[4])
> > #ABD
> >
> > names(Cubist$Expression$Disease2[4])
> > #ABD
> >
> > Now I need to built the final matrices for every genes (1000) that I will
> > use for CORREP function.
> >
> > Is there a way to extract directly the first column (first gene) for all
> > Diseases (80)  from Cubist$Expression? or
> >
>
> I don't understand most your question, but the above seems to be straight
> forward.  Here's a toy example:
>
> # make a list of matrices, each with nCol columns and differing
> # number of rows, nRow
> nCol <- 3
> nRow <- sample(3:10, 5)
> x <- lapply(nRow, function(x, nc) {matrix(x:(x + nc*x - 1), ncol = nc,
> nrow = x)}, nCol)
> x
>
> # make a simple function to get a single column from a matrix
> getColumn <- function(x, colNum) {
>    return(x[,colNum])
> }
>
> # use the function to get the column from each matrix
> col1 <- lapply(x, getColumn, 1)
> col1
>
> Does that help answer this part of your question?  If not, you may need to
> create a very small example of your data and post it here using the head()
> and dput() functions.
>
> Ben
>
>
>
> > I need to built 1000 matrices with 80 columns and unequal rows?
> >
> > Cublist$Diseases <- vector("list", 1)
> >
> > for (k in 1:1000){
> > for (i in 1:80){
> >
> > Cublist$Diseases[[gene[k] ]] <- Cubist$Expression[[Diseases[i] ]][k]
> > }
> >
> > }
> >
> > This double loops is time consuming...Is there a way to do this faster?
> >
> > Thanks,
> > karim
> >  Ô__
> > c/ /'_;~~~~kmezhoud
> > (*) \(*)   ⴽⴰⵔⵉⵎ  ⵎⴻⵣⵀⵓⴷ
> > http://bioinformatics.tn/
> >
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> >
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>
>

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