[R] Help with SOM membership

Edgar Acuna edgar at cs.uprm.edu
Fri Jun 10 02:30:42 CEST 2005


Hi,
Try allt.som$visual
Edgar Acuna
UPRM

On Thu, 9 Jun 2005, Ken Termiso wrote:

> Hi all,
>
> I originally posted this to the bioconductor group, but maybe it's better
> suited to the r-help...
>
> I'm using som() to partition samples of gene expression data into clusters.
> The point is to classify control vs. experimental cases (sample clustering).
> The original matrix was 22283 x 8. The 8 samples have 4 controls and 4
> experimentals.
>
> I transposed the matrix so that its dim are 8 x 22283, and called that
> "allt." Using the normalize() function from som library, I scaled the data
> to have mean zero and variance 1.
>
> allt.som <- som(allt, xdim=5, ydim=5, topol="hexa", neigh="bubble", alpha=1)
> plot(allt.som)
>
> What I cannot figure out how to do is how to determine where each sample has
> clustered, since the plot that i'm using does not include labels...I also
> tried str(allt.som) but cannot determine which attribute calls where each
> sample has gone...all I would like to know is where samples are being placed
> in the SOM grids, to make sure that the controls cluster together and exps
> cluster together. (Also I would eventually like to cluster the genes with
> SOM and also like to know which genes are clustered in which grids, which is
> the same problem as I have with the samples).
>
> Thanks in advance,
> Ken
>
>
> >str(allt.som)
> List of 16
> $ data      : num [1:8, 1:22277] 1167 1282 1561 1398 1581 ...
>   ..- attr(*, "dimnames")=List of 2
>   .. ..$ : chr [1:8] "m577con" "m577exp" "m578con" "m578exp" ...
>   .. ..$ : chr [1:22277] "1007_s_at" "1053_at" "117_at" "121_at" ...
> $ code      : matrix [1:25, 1:22277] 1050 1222 1411 1504 1722 ...
>   ..- attr(*, "class")= chr "matrix"
> $ visual    :`data.frame':     8 obs. of  3 variables:
>   ..$ x     : num [1:8] 0 1 3 2 3 4 2 1
>   ..$ y     : num [1:8] 1 2 0 1 3 3 2 4
>   ..$ qerror: num [1:8] 6472 8396 7574 7856 6969 ...
> $ qerror    : num 6e+08
> $ init      : chr "linear"
> $ alpha     : chr "inverse"
> $ neigh     : chr "bubble"
> $ topol     : chr "hexa"
> $ alpha0    : num [1:2] 1 0.5
> $ radius0   : num [1:2] 5 3
> $ rlen      : num [1:2] 16 80
> $ xdim      : num 5
> $ ydim      : num 5
> $ err.radius: num 1
> $ inv.alp.c : num [1:2] 0.16 0.8
> $ code.sum  :`data.frame':     25 obs. of  3 variables:
>   ..$ x   : num [1:25] 0 1 2 3 4 0 1 2 3 4 ...
>   ..$ y   : num [1:25] 0 0 0 0 0 1 1 1 1 1 ...
>   ..$ nobs: int [1:25] 0 0 0 1 0 1 0 1 0 0 ...
> - attr(*, "class")= chr "som"
>
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