Hi,
Did you try other epsilon values like 1.9, 2.0, 2.1, 2.2 or 2.5, 2.6?
On Fri, Apr 19, 2013 at 1:44 PM, Amparo Garcia Lopez <
Amparo.GarciaLopez.unige.ch> wrote:
> Hi Dan,
>
> thanks for your reply.
>
> So I tried using the sieve option, and I got the same thing: all frames in
> one cluster. I tried using epsilon (2.3) instead of cluster count and then
> it created ~200 representative pdb's!
>
> Yes, I read the paper you're mentioning back in the day. I'll have to read
> it again and try some other method, as the average linking isn't making
> much sense for me. Any suggestions on what to try first?
>
> Thanks very much,
> Amparo
>
>
> Amparo Garcia-Lopez, Ph.D.
>
> Pharmaceutical Biochemistry
> School of Pharmaceutical Sciences
> University of Geneva
> Quai Ernest-Ansermet 30
> 1211 Genève 4 - Switzerland
>
> Tel: +41 (0)22 379 3376
> Fax: +41 (0)22 379 3360
>
> e-mail: Amparo.GarciaLopez.unige.ch
> ________________________________________
> From: Daniel Roe [daniel.r.roe.gmail.com]
> Sent: 15 April 2013 16:09
> To: AMBER Mailing List
> Subject: Re: [AMBER] clustering places all frames in one cluster
>
> Hi,
>
> On Mon, Apr 15, 2013 at 2:26 AM, Amparo Garcia Lopez
> <Amparo.GarciaLopez.unige.ch> wrote:
> > what I get is 10 clusters in which, 19,991 frames are in the first
> cluster (c0), and the rest of the clusters have only one point in them.
> >
> > This is not possible, I've done clustering of this RNA before using diff
> settings (e.g., collecting 1 frame every 100 instead of every 20) and I get
> clusters with nicely distributed occurences.
> > what do you think I have done wrong? Maybe 10 clusters is too much,
> maybe collecting 1 every 20 is not a good idea? We are talking about a
> trajectory of 400 ns here.
>
> Clustering is very much an art form; there really is no
> one-size-fits-all procedure for clustering every trajectory. Settings
> that work well on one system may give poor results on another (as you
> have seen). Have you tried varying epsilon instead of cluster count,
> or trying some of the other clustering algorithms available in ptraj?
> You can also try the 'sieve' option, which will first cluster on a
> reduced set (similar to the offset method) then add frames back in
> based on similarity to cluster centroids. If you haven't yet, I highly
> recommend you read through the clustering journal article from Shao &
> Cheatham et al., JCTC (2007) v 3 p 2312-2334.
>
> -Dan
>
> --
> -------------------------
> Daniel R. Roe, PhD
> Department of Medicinal Chemistry
> University of Utah
> 30 South 2000 East, Room 201
> Salt Lake City, UT 84112-5820
> http://home.chpc.utah.edu/~cheatham/
> (801) 587-9652
> (801) 585-9119 (Fax)
>
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--
With regards
Vaibhav A. Dixit
Ph.D.
Department of Medicinal Chemistry
Natl. Inst. Pharm. Edu. & Res. (NIPER)
Sector 67, Phase X, S.A.S. Nagar (Mohali)
Punjab -160 062 INDIA
Phone (Mobile): +919915214408, +91-7709129400.
E-mail: vaibhavadixit.gmail.com
www.niper.nic.in
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Received on Sun Apr 21 2013 - 22:30:03 PDT
