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 ? 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 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
?__
c/ /'_;~~~~kmezhoud
(*) \(*) ????? ??????
http://bioinformatics.tn/
[[alternative HTML version deleted]]
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 ? 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 > ?__ > c/ /'_;~~~~kmezhoud > (*) \(*) ????? ?????? > http://bioinformatics.tn/ > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
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 ?__ c/ /'_;~~~~kmezhoud (*) \(*) ????? ?????? 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 ? 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 > > ?__ > > c/ /'_;~~~~kmezhoud > > (*) \(*) ????? ?????? > > http://bioinformatics.tn/ > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > >[[alternative HTML version deleted]]