Dear All,
I am facing the task to extract data from array to table. here an example
of array.
##Get A list of Matrices with unequal rows
Disease <- NULL
Diseases <- NULL
ListMatByGene <- NULL
for(i in 1:3){
Disease[[i]] <-matrix(sample(-30:30,25+(5*
i)),5+i)
rownames(Disease[[i]]) <- paste0("Sample",1:(5+i))
colnames(Disease[[i]]) <- paste0("Gene",1:5)
D <- paste0("Disease",i)
Diseases[[D]] <- Disease[[i]]
}
## get the same Column from all matrices
getColumn <- function(x, colNum, len = nrow(x)){
y <- x[,colNum]
length(y) <- len
y
}
## get Matrices by the same columns of the list of matrices
getMatrices <- function(colNums, dataList = x){
# the number of rows required
n <- max(sapply(dataList, nrow))
lapply(colNums, function(x, dat, n) { # iterate along requested columns
do.call(cbind, lapply(dat, getColumn,x, len=n)) # iterate along
input data list
}, dataList, n)
}
## Rotate the list of matrices by 90?
G <- paste0("Gene",1:5)
ListMatByGene[G] <- getMatrices(c(1:ncol(Diseases[[1]])),dataList=Diseases)
## get Disease correlation by gene
DiseaseCorrelation <- lapply(ListMatByGene,function(x)
cor(x,use="na",
method="spearman"))
##convert the list of Matrices to array
ArrayDiseaseCor <- array(unlist(DiseaseCorrelation), dim
c(nrow(DiseaseCorrelation[[1]]), ncol(DiseaseCorrelation[[1]]),
length(DiseaseCorrelation)))
dimnames(ArrayDiseaseCor) <- list(names(Diseases), names(Diseases),
colnames(Diseases[[1]]))
## Select only correlation bigger than 0.5 from the array
FilterDiseaseCor <- apply(ArrayDiseaseCor,MARGIN=c(1,2) ,function(x)
x[abs(x)>0.5])
## Final result
FilterDiseaseCor
Disease1 Disease2 Disease3
Disease1 Numeric,5 Numeric,2 -0.9428571
Disease2 Numeric,2 Numeric,5 Numeric,2
Disease3 -0.9428571 Numeric,2 Numeric,5
Question is:
How can get a table as:
D1 D2 Cor Gene
Disease1 Disease2 -0.94 Gene2
Disease1 Disease2 0.78 Gene4
Disease3 Disease2 0.5 Gene5
...
and
Disease1 Disease2 Disease3
Disease1 5 1 0
Disease2 1 5 3
Disease3 0 3 5
Or in general, How can I extract data from Array to Table?
Thanks
Karim
[[alternative HTML version deleted]]
Make use of the plyr and reshape2 package (both on CRAN): library(plyr) d<-adply(ArrayDiseaseCor, 1:2) # adply calls function identity by default d<-melt(d) d<-subset(d,value>.5) head(d) You will have to rename columns, or adjust arguments in melt/adply. Note: use set.seed before sampling for reproducible code! Best, S. On 11 February 2015 at 17:11, Karim Mezhoud <kmezhoud at gmail.com> wrote:> Dear All, > I am facing the task to extract data from array to table. here an example > of array. > > ##Get A list of Matrices with unequal rows > > Disease <- NULL > Diseases <- NULL > ListMatByGene <- NULL > for(i in 1:3){ > > Disease[[i]] <-matrix(sample(-30:30,25+(5* > i)),5+i) > rownames(Disease[[i]]) <- paste0("Sample",1:(5+i)) > colnames(Disease[[i]]) <- paste0("Gene",1:5) > > D <- paste0("Disease",i) > Diseases[[D]] <- Disease[[i]] > } > > > ## get the same Column from all matrices > getColumn <- function(x, colNum, len = nrow(x)){ > y <- x[,colNum] > length(y) <- len > y > } > > ## get Matrices by the same columns of the list of matrices > getMatrices <- function(colNums, dataList = x){ > # the number of rows required > n <- max(sapply(dataList, nrow)) > lapply(colNums, function(x, dat, n) { # iterate along requested columns > do.call(cbind, lapply(dat, getColumn,x, len=n)) # iterate along > input data list > }, dataList, n) > } > > ## Rotate the list of matrices by 90? > G <- paste0("Gene",1:5) > ListMatByGene[G] <- getMatrices(c(1:ncol(Diseases[[1]])),dataList=Diseases) > > ## get Disease correlation by gene > DiseaseCorrelation <- lapply(ListMatByGene,function(x) cor(x,use="na", > method="spearman")) > > ##convert the list of Matrices to array > ArrayDiseaseCor <- array(unlist(DiseaseCorrelation), dim > c(nrow(DiseaseCorrelation[[1]]), ncol(DiseaseCorrelation[[1]]), > length(DiseaseCorrelation))) > dimnames(ArrayDiseaseCor) <- list(names(Diseases), names(Diseases), > colnames(Diseases[[1]])) > > ## Select only correlation bigger than 0.5 from the array > FilterDiseaseCor <- apply(ArrayDiseaseCor,MARGIN=c(1,2) ,function(x) > x[abs(x)>0.5]) > > ## Final result > FilterDiseaseCor > > Disease1 Disease2 Disease3 > Disease1 Numeric,5 Numeric,2 -0.9428571 > Disease2 Numeric,2 Numeric,5 Numeric,2 > Disease3 -0.9428571 Numeric,2 Numeric,5 > > > Question is: > How can get a table as: > > D1 D2 Cor Gene > Disease1 Disease2 -0.94 Gene2 > Disease1 Disease2 0.78 Gene4 > Disease3 Disease2 0.5 Gene5 > ... > > and > Disease1 Disease2 Disease3 > Disease1 5 1 0 > Disease2 1 5 3 > Disease3 0 3 5 > > Or in general, How can I extract data from Array to Table? > > Thanks > Karim > > [[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.
see inline On 12 February 2015 at 09:10, Sven E. Templer <sven.templer at gmail.com> wrote:> Make use of the plyr and reshape2 package (both on CRAN): >I forgot: library(reshape2)> library(plyr) > d<-adply(ArrayDiseaseCor, 1:2) > # adply calls function identity by default > d<-melt(d) > d<-subset(d,value>.5) > head(d) > > You will have to rename columns, or adjust arguments in melt/adply. > Note: use set.seed before sampling for reproducible code! > > Best, S. > > On 11 February 2015 at 17:11, Karim Mezhoud <kmezhoud at gmail.com> wrote: >> Dear All, >> I am facing the task to extract data from array to table. here an example >> of array. >> >> ##Get A list of Matrices with unequal rows >> >> Disease <- NULL >> Diseases <- NULL >> ListMatByGene <- NULL >> for(i in 1:3){ >> >> Disease[[i]] <-matrix(sample(-30:30,25+(5* >> i)),5+i) >> rownames(Disease[[i]]) <- paste0("Sample",1:(5+i)) >> colnames(Disease[[i]]) <- paste0("Gene",1:5) >> >> D <- paste0("Disease",i) >> Diseases[[D]] <- Disease[[i]] >> } >> >> >> ## get the same Column from all matrices >> getColumn <- function(x, colNum, len = nrow(x)){ >> y <- x[,colNum] >> length(y) <- len >> y >> } >> >> ## get Matrices by the same columns of the list of matrices >> getMatrices <- function(colNums, dataList = x){ >> # the number of rows required >> n <- max(sapply(dataList, nrow)) >> lapply(colNums, function(x, dat, n) { # iterate along requested columns >> do.call(cbind, lapply(dat, getColumn,x, len=n)) # iterate along >> input data list >> }, dataList, n) >> } >> >> ## Rotate the list of matrices by 90? >> G <- paste0("Gene",1:5) >> ListMatByGene[G] <- getMatrices(c(1:ncol(Diseases[[1]])),dataList=Diseases) >> >> ## get Disease correlation by gene >> DiseaseCorrelation <- lapply(ListMatByGene,function(x) cor(x,use="na", >> method="spearman")) >> >> ##convert the list of Matrices to array >> ArrayDiseaseCor <- array(unlist(DiseaseCorrelation), dim >> c(nrow(DiseaseCorrelation[[1]]), ncol(DiseaseCorrelation[[1]]), >> length(DiseaseCorrelation))) >> dimnames(ArrayDiseaseCor) <- list(names(Diseases), names(Diseases), >> colnames(Diseases[[1]])) >> >> ## Select only correlation bigger than 0.5 from the array >> FilterDiseaseCor <- apply(ArrayDiseaseCor,MARGIN=c(1,2) ,function(x) >> x[abs(x)>0.5]) >> >> ## Final result >> FilterDiseaseCor >> >> Disease1 Disease2 Disease3 >> Disease1 Numeric,5 Numeric,2 -0.9428571 >> Disease2 Numeric,2 Numeric,5 Numeric,2 >> Disease3 -0.9428571 Numeric,2 Numeric,5 >> >> >> Question is: >> How can get a table as: >> >> D1 D2 Cor Gene >> Disease1 Disease2 -0.94 Gene2 >> Disease1 Disease2 0.78 Gene4 >> Disease3 Disease2 0.5 Gene5 >> ... >> >> and >> Disease1 Disease2 Disease3 >> Disease1 5 1 0 >> Disease2 1 5 3 >> Disease3 0 3 5 >> >> Or in general, How can I extract data from Array to Table? >> >> Thanks >> Karim >> >> [[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.