[R] conversion of data for use within barchart

[Deepayan Sarkar]

On 7/2/08, Karin Lagesen <karinlag at studmed.uio.no> wrote:
>
>
>  I have a data matrix like this:
>
>
>  > data[1:10,]
>    aaname grp   cluster count
>  1     Ala All Singleton   432
>  2     Arg All Singleton  1239
>  3     Asn All Singleton   396
>  4     Asp All Singleton   152
>  5     Cys All Singleton   206
>  6     Gln All Singleton   370
>  7     Glu All Singleton   211
>  8     Gly All Singleton   594
>  9     His All Singleton   213
>  10    Ile All Singleton    44
>
>  where the cluster column has three levels.
>
>  > levels(data$cluster)
>  [1] "Array"     "Singleton" "rRNA"
>  >
>
>  Now, I would like to plot this like this:
>
>  barchart(aaname~count|grp, group = cluster, data = data, stack = TRUE)
>
>  I am thus using the cluster as the grouping.
>
>  I would like to plot the relative abundance within each grouping, such
>  that the max level in my plot always is one (or 100). This would for
>  instance mean for the Ala in the All grp that the Singleton cluster
>  consitute lets say 40% of the Ala in the All grp, wheras the Singleton
>  and rRNA makes up 20% each. In this case I would get in my plot a
>  Singleton stretching to 40%, whereas the other two would be 20% each,
>  all in all making 100%.
>
>  I am uncertain of whether I am managing to describe what I want, so I
>  hope somebody understands what I want!

So you basically need to compute the sum(count) within clusters, and
divide by those counts. Consider using ave(). For example:

> foo <- data.frame(g = gl(3, 3), count = rpois(9, lambda=20))
> foo
  g count
1 1    14
2 1    16
3 1    20
4 2    21
5 2    24
6 2    16
7 3    15
8 3    24
9 3    12
> with(foo, ave(count, g, FUN = sum))
[1] 50 50 50 61 61 61 51 51 51
> foo$gsum <- with(foo, ave(count, g, FUN = sum))
> foo
  g count gsum
1 1    14   50
2 1    16   50
3 1    20   50
4 2    21   61
5 2    24   61
6 2    16   61
7 3    15   51
8 3    24   51
9 3    12   51

-Deepayan