Running hierarchical single linkage clustering on R

Hi

Currently i am a first time user of R Software.

I am trying to run a hierachical clustering of binding site similarities of some ligands.. I need to use Single Linkage. I am trying to run a command line version of the program. I already have a distance matrix of similarity scores available as a text file. The output of clusters needs to printed as a dendrogram. Can I choose the option to print the cluster results as a text file , as well as to view the tree as a PDF? Has anyone done something similar to this?

Any help will be great

Thanks!

Shalini

http://www.flamingtext.com/hmail.html

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From: Titus Brown <[email protected]>
Reply-To: [email protected],General discussions about software development in bioinformatics <[email protected]>
To: ibtissem grissa <[email protected]>
CC: General discussions about software development in bioinformatics <[email protected]>,[email protected]
Subject: Re: [Biodevelopers] download bacterial genomes
Date: Mon, 19 Jun 2006 08:52:06 -0700
>On Mon, Jun 19, 2006 at 05:45:22PM +0200, ibtissem grissa wrote:
>-> >
>-> >What about:
>-> >
>-> >ftp://ftp.ncbi.nlm.nih.gov/genomes/Bacteria
>->
>-> yes, but I found only complete and published genomes there,
>-> what I need is to have the maximum of genomes, even if they are not
>-> completed or
public.
>->
>-> ? Or you could look at TIGR and JGI sites; JGI in particular may have a
>-> >few that aren't anywhere else.
>->
>->
>-> And I need to download them by an automatic way, so how could I check if
>-> they don't exist elsewhere automatically.
>->
>-> Furthermore, I want to have all the information about genomes, and
>-> especially the taxon classification of the organism
>-> (Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacteriales;
>-> Enterobacteriaceae)
>
>I don't actually know of an electronic source for that information,
>although it may be possible to retrieve it from NCBI taxonomy. I'm sure
>if you browse around NCBI or TIGR you can find it.
>
>Most microbial genomes get finished relatively quickly, because
they're
>so *tiny* ;). I don't think there'll be much of a lag, so you might
>want to just try out your algorithm on the already finished ones.
>
>You can't get non-public ones ;).
>
>In any case, if you do find a good source for all this information, please
>repost it to this list (or send it to me personally ;). I'd be very
>interested.
>
>thanks,
>--titus
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