minoo minoo - 3 months ago 13
R Question

using separate matrices in a loop and saving the results in a data frame

I have a few matrices that all of them are the same in number of rows and columns and dimanames of them are exactly the same too. I read them like this for example

a<-read.csv("a.txt",row.names = 1,header=T,sep="\t")
b<-read.csv("b.txt",row.names = 1,header=T,sep="\t")
c<-read.csv("c.txt",row.names = 1,header=T,sep="\t")
d<-read.csv("d.txt",row.names = 1,header=T,sep="\t")
e<-read.csv("e.txt",row.names = 1,header=T,sep="\t")

Now I want to get similarity index between a & b, a & c,...,b & c, ..., c & d, d
& e using this code


jaccard.index<-birewire.similarity( a,b)

Then I want to save the result as a data frame like this for example

mat1 mat2 simil.index
a b 0.9142
a c 0.8126
a d 0.5066
b e 0.9526

I don't know how can I use these separate matrices in a loop and saving the result like that. Anyone help me on this problem?


Prepare the function to compute pairwise similarities

myfun <- function(x, y) {

  birewire.similarity(eval(parse(text = x)), eval(parse(text = y)))


Build the possible combinations (you said your matrices are named as the first 5 letters of the alphabet, but you can put any names in place of letters[1:5]):

myletters <- combn(letters[1:5], 2)

Build the dataframe binding by column the combinations and the results of the function that is applied to such combinations:

           simil.index = mapply(myfun, myletters[1,], myletters[2,]))