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Convert and save distance matrix to a specific format

I got a distance matrix with the following steps:

x <- read.table(textConnection('
     t0 t1 t2
 aaa  0  1  0
 bbb  1  0  1
 ccc  1  1  1
 ddd  1  1  0
 ' ), header=TRUE)

As such x is a data frame with column and row headers

    t0 t1 t2
aaa  0  1  0
bbb  1  0  1
ccc  1  1  1
ddd  1  1  0

require(vegan)
d <- vegdist(x, method="jaccard")

The distance matrix d is obtained as follows:

          aaa       bbb       ccc
bbb 1.0000000                    
ccc 0.6666667 0.3333333          
ddd 0.5000000 0.6666667 0.3333333

By typing str(d), I found it is not a ordinary table nor csv format.

Class 'dist'  atomic [1:6] 1 0.667 0.5 0.333 0.667 ...
  ..- attr(*, "Size")= int 4
  ..- attr(*, "Labels")= chr [1:4] "aaa" "bbb" "ccc" "ddd"
  ..- attr(*, "Diag")= logi FALSE
  ..- attr(*, "Upper")= logi FALSE
  ..- attr(*, "method")= chr "jaccard"
  ..- attr(*, "call")= language vegdist(x = a, method = "jaccard")

I want to covert the distance matrix to a 3 columns with new headers and save it as a csv file as follows:

c1  c2  distance
aaa bbb 1.000
aaa ccc 0.6666667
aaa ddd 0.5
bbb ccc 0.3333333
bbb ddd 0.6666667
ccc ddd 0.3333333
like image 854
Catherine Avatar asked Apr 28 '11 03:04

Catherine


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2 Answers

This is quite doable using base R functions. First we want all pairwise combinations of the rows to fill the columns c1 and c2 in the resulting object. The final column distance is achieved by simply converting the "dist" object d into a numeric vector (it already is a vector but of a different class).

The first step is done using combn(rownames(x), 2) and the second step via as.numeric(d):

m <- data.frame(t(combn(rownames(x),2)), as.numeric(d))
names(m) <- c("c1", "c2", "distance")

Which gives:

> m
   c1  c2  distance
1 aaa bbb 1.0000000
2 aaa ccc 0.6666667
3 aaa ddd 0.5000000
4 bbb ccc 0.3333333
5 bbb ddd 0.6666667
6 ccc ddd 0.3333333

To save as a CSV file, write.csv(m, file = "filename.csv").

like image 181
Gavin Simpson Avatar answered Sep 29 '22 11:09

Gavin Simpson


you can do this by combining melt from reshape package, upper.tri etc.:

> library(reshape)
> m <- as.matrix(d)
> m
          aaa       bbb       ccc       ddd
aaa 0.0000000 1.0000000 0.6666667 0.5000000
bbb 1.0000000 0.0000000 0.3333333 0.6666667
ccc 0.6666667 0.3333333 0.0000000 0.3333333
ddd 0.5000000 0.6666667 0.3333333 0.0000000
> m2 <- melt(m)[melt(upper.tri(m))$value,]
> names(m2) <- c("c1", "c2", "distance")
> m2
    c1  c2  distance
5  aaa bbb 1.0000000
9  aaa ccc 0.6666667
10 bbb ccc 0.3333333
13 aaa ddd 0.5000000
14 bbb ddd 0.6666667
15 ccc ddd 0.3333333
like image 29
kohske Avatar answered Sep 29 '22 10:09

kohske