Re: [AMBER] cluster analysis using cpptraj

From: Sowmya Indrakumar <soemya.kemi.dtu.dk>
Date: Mon, 25 Sep 2017 09:55:57 +0000

Hi Thomas,
Thank you very much for you're suggestions.
I initially did tried with with the following parameters :
> Minimum pts to form cluster= 25
> Cluster distance criterion= 0.900
> sieve frame 10 then I have over 2000 frames.
I got clusters with Hierarchical agglomerative-average linkage algorithm. I attached the plot in my previous email.
As suggested. I will also see have a look at the 2D-RMSD plot.
regards
sowmya
________________________________________
From: Thomas Cheatham [tec3.utah.edu]
Sent: Monday, September 25, 2017 11:47 AM
To: AMBER Mailing List
Subject: Re: [AMBER] cluster analysis using cpptraj

> I am doing cluster analysis using the following script from:
> http://www.amber.utah.edu/AMBER-workshop/London-2015/Cluster/

One problem with following a workshop script is that you do not have the
instructors in the audience to help out and often such scripts are
explanatory for a particular data set and not necessarily generally
useful. Note that there are many clustering approaches, each with
different assumptions.

The first thing I would do is create a 2D-RMSD plot to see if there are
clear clusters and to show me what to expect. If there are no blocks
visible, likely the RMSD vs. time is just increasing and you are not
re-visiting conformations.

Try to understand what the algorithms are doing...

In your case, you have sieve 100 so only 200 frames are looked at the for
the clustering. You have minpoints of 25; since no clusters are being
formed, in those 200 frames 25 of them (1/8th) are not falling into a
single cluster (hence no cluster is formed). Finally, the time to do the
clustering was only 10 s (compared to much longer for reading trajectory)
and memory usage was low, so why not cluster more frames? My guess is
that your RMSD is increasing over time... I would try sieve 10.

Also, other clustering algorithms do not have minimum sizes; try
hierarchical or k-means or some other algorithm too. Clustering is kind
of an art and you need to experiment a bit...

--tec3

> Minimum pts to form cluster= 25
> Cluster distance criterion= 0.900

(maybe set cluster distance criterion higher?)

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Received on Mon Sep 25 2017 - 03:00:04 PDT
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