# [R] Cube of Matrices or list of Matrices

Karim Mezhoud kmezhoud at gmail.com
Mon Jan 19 23:17:53 CET 2015

```Thanks Ben.
R documentation is very short.

How can obtain:
z <- list (Col1, Col2, Col3, Col4......)?

Thanks

Ô__
c/ /'_;~~~~kmezhoud
(*) \(*)   ⴽⴰⵔⵉⵎ  ⵎⴻⵣⵀⵓⴷ
http://bioinformatics.tn/

On Mon, Jan 19, 2015 at 8:22 PM, Ben Tupper <btupper at bigelow.org> wrote:

> Hi again,
>
> On Jan 19, 2015, at 1:53 PM, Karim Mezhoud <kmezhoud at gmail.com> wrote:
>
> 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?
>
>
> Perhaps best is to determine the maximum number of rows required first,
> then force each subset to have that length.
>
> # make a list of matrices, each with nCol columns and differing
> # number of rows
> 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, len = nrow(x)) {
>    y <- x[,colNum]
>    length(y) <- len
>    y
> }
>
> # what is the maximum number of rows
> n <- max(sapply(x, nrow))
>
> # use the function to get the column from each matrix
> col1 <- lapply(x, getColumn, 1, len = n)
> col1
>
> do.call(cbind, col1)
>       [,1] [,2] [,3] [,4] [,5]
>  [1,]    3    8    5    7    9
>  [2,]    4    9    6    8   10
>  [3,]    5   10    7    9   11
>  [4,]   NA   11    8   10   12
>  [5,]   NA   12    9   11   13
>  [6,]   NA   13   NA   12   14
>  [7,]   NA   14   NA   13   15
>  [8,]   NA   15   NA   NA   16
>  [9,]   NA   NA   NA   NA   17
>
> Ben
>
> Thanks
> Karim
>
>
>   Ô__
>  c/ /'_;~~~~kmezhoud
> (*) \(*)   ⴽⴰⵔⵉⵎ  ⵎⴻⵣⵀⵓⴷ
> http://bioinformatics.tn/
>
>
>
> 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
>>
>> 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/
>> >
>> >       [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
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>> > https://stat.ethz.ch/mailman/listinfo/r-help
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>> <http://www.r-project.org/posting-guide.html>
>> > and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
> Ben Tupper
> Bigelow Laboratory for Ocean Sciences
> 60 Bigelow Drive, P.O. Box 380
> East Boothbay, Maine 04544
> http://www.bigelow.org
>
>
>
>
>
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>

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