Hi Ayesha,
hclust is a way to go (much better then trying to invent the wheel here).

Please add what you used to create:
distA

And create a sample data set to show us what you did, using
dput

Best,
Tal



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On Fri, May 28, 2010 at 2:41 AM, Ayesha Khan <ayesha.diamondash@gmail.com>wrote:

> i have a matrix with the following dimensions
> 136   3
>
> and it looks something like
>
>         [,1] [,2]     [,3]
>  [1,]  402  675 1.802758
>  [2,]  402  696 1.938902
>  [3,]  402  699 1.994253
>  [4,]  402  945 1.898619
>  [5,]  424  470 1.812857
>  [6,]  424  905 1.816345
>  [7,]  470  905 1.871252
>  [8,]  504  780 1.958191
>  [9,]  504  848 1.997111...............
>
> ................................................................................
> so you get the idea. I want to group similar items in one group/cluster
> following the "friends of friends" approach. I tried doing
>
> distclust <- hclust(distA,method="single")
> However, I got the following error.
>
> Error in if (n < 2) stop("must have n >= 2 objects to cluster") :  argument
> is of length zero
> which probably means there's something wrong with my input here. Is there
> another way of doing this kind of clustering without getting into all the
>  looping and ifelse etc. Basically, if 402 is close to 675,696,and699 and
> thus fall in cluster A then all items close to 675,696,and 699 should also
> fall into the same cluster A following a friends of friedns strategy.
> Any help would be highly appreciated.
>
> --
> Ayesha Khan
>
> MS Bioengineering
> Dept. of Bioengineering
> Rice University, TX
>
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>
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>

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