[Biodevelopers] Any simple clustering program for HierarchicalSingle Linkage available?

Asim Siddiqui asims at bcgsc.ca
Sun Jun 18 19:21:54 EDT 2006


Hi,
 
Actually, OC stdout will contain the information you're looking for. Use the "cut" option. The output isn't that friendly to parse, but it can be done.
 
Asim
 
oc dis complete id cut 20 < test.dis
Reading Upper Diagonal
Read: 7 Entries
CPU time: 0.000000 seconds
Setting up unclust
Setting up notparent
Setting up clust
CPU time: 0.000000 seconds
Complete linkage on distance
Doing Cluster Analysis...
## 1 20 2
Third Sixth
## 0 20 2
First Seventh

UNCLUSTERED ENTITIES
Second
Fourth
Fifth
Total CPU time: 0.000000 seconds


________________________________

From: biodevelopers-bounces+asims=bcgsc.ca at bioinformatics.org on behalf of Shalini Sridhar
Sent: Sat 6/17/2006 11:52 PM
To: biodevelopers at bioinformatics.org
Subject: [Biodevelopers] Any simple clustering program for HierarchicalSingle Linkage available? 



Hello All,

I need a simple , freely downloadable , Clustering program , that will cluster a large number of records (>10,000) using Hierarchical Clustering Methods, and using Single Linkage Clustering Technique. 

I would like to cluster a large number of proteins based on a similarity score that will be used as input and to output a tree in the form of a text file.

This program needs to be run from command line, prefereably a C executable from a UNIX machine. The input would be a text file of a distance matrix and the output will also be a text file of clusters or dendrograms.

I came across OC - Geoffery Barton - University of Dundee, that fits my required description, however the output is just a PS file, and thus cannot be manipulated further.

I also came across Eisen Lab's - CLuster3.0 , however, this is more complicated and used for mostly microarray data, since the input and output file fits the requirement for microarray sets.

Could someone please suggest me a simple program that would fit my description required? Would really appreciate it.

Thank you.

Shalini Sridhar

MRes.Bioinformatics and Computational Biology, Univ of Leeds,Leeds.


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