Thanks Ben. I need to learn more about apply. Have you a link or tutorial about apply. 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 <btup...@bigelow.org> wrote: > Hi again, > > On Jan 19, 2015, at 1:53 PM, Karim Mezhoud <kmezh...@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.bigh...@gmail.com> wrote: > >> Hi, >> >> On Jan 18, 2015, at 4:36 PM, Karim Mezhoud <kmezh...@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/ >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@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 >> <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 > > > > > > > > > [[alternative HTML version deleted]] ______________________________________________ R-help@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.
