Dear Daniel
>> Each of the dots in the principal component projection plots in Figs 3/4
represent the PC projection value for PCs 1 and 2 for a single frame.
Sorry if I did not explain my problem correctly. I have problem, rather
could not understand, in obtaining a plot for EV1 vs Residue/Atom
displacement (Figure 3B) and what should be the matrix dimension
calculation/multiplication. (The thing is EV1 has 3N dimension and on x
axis I have just N atoms somehow averaged on F frames)
Thanks again
On Thu, May 8, 2014 at 4:04 PM, Daniel Roe <daniel.r.roe.gmail.com> wrote:
> Hi,
>
> The projection of a coordinate frame along a certain eigenvector
> essentially tells you how much that frame contributes to that
> particular principal component. Each of the dots in the principal
> component projection plots in Figs 3/4 represent the PC projection
> value for PCs 1 and 2 for a single frame. In each frame you have N
> atoms, but 3N coordinates, which matches the dimensions of the
> covariance matrix.
>
> Also note that you have to be careful when comparing eigenvectors
> obtained from covariance matrices of different trajectories, as they
> are not guaranteed to be the same. I didn't see any discussion of this
> in my (admittedly brief) glance at the referenced paper. You can
> either check if the eigenvectors are aligned manually, or generate a
> covariance matrix from the combined trajectories, then calculate your
> projections for each trajectory separately.
>
> Hope this helps,
>
> -Dan
>
> On Wed, May 7, 2014 at 4:27 PM, newamber list <newamberlist.gmail.com>
> wrote:
> > Hi
> >
> >>> If you are referring to figures 3/4 in the above reference
> >
> > Yes, e.g. Fig 3A and 3B. I can get 3A as:
> >
> > crdaction crd1 projection modes evecs.dat out myproj.txt beg 1 end 2
> > :1-328.N. I have some confusion about calculation. Once you get
> > Eigenvectors for Covar Matrix of 3Nx3N dimension then you calculate new
> > data as e.g. just for EV1 and EV2 as:
> >
> > #Fx2 #2x3N
> >
> > |(xi1-Xi) (xk-Xk)| |EV1 in Row|
> > : : | |EV2 in Row|
> > : : |
> > |(xiF-Xi) (xiF-xk)|
> >
> > where x represents coordinate and X average. Does xi and xk would
> > necessarily mean the first and second dimension only (which happens to be
> > first two coordinates?) I know its wrong how xi and xj is chosen?
> >
> > Still for Figure 3B I don't understand how its calculated as Eigenvector
> > has a dimension of 3N but I have NxF atoms (where N is number of atoms
> and
> > F is Number of frames)
> >
> > thanks
> > Jiom
> >
> >
> >
> >
> > On Wed, May 7, 2014 at 3:52 PM, Daniel Roe <daniel.r.roe.gmail.com>
> wrote:
> >
> >> On Tue, May 6, 2014 at 10:21 PM, newamber list <newamberlist.gmail.com>
> >> wrote:
> >> > Its working now but I am not sure if this is how people
> calculate/present
> >> > their results. Usually in papers they show displacements along one
> >> > eigenvector (e.g.
> >> >
> >>
> http://pubs.rsc.org/en/Content/ArticleLanding/2014/MB/c4mb00177j#!divAbstract
> >>
> >> If you are referring to figures 3/4 in the above reference, then what
> >> you want to calculate is the projection of your coordinates along
> >> certain eigenvectors - see the 'projection' command in CPPTRAJ. The
> >> 'modes displ' just calculates total XYZ displacement for all
> >> eigenvectors.
> >>
> >> -Dan
> >>
> >> > )
> >> >
> >> > I get displX, Y and Z but I was expecting some net displacement which
> >> > simply I think should be sqrt(x^2+y^+z^2) and also for each individual
> >> > eigenvector I should do something like this:
> >> >
> >> > modes name evecs.dat displ out dis1.dat beg 1 end 1
> >> > modes name evecs.dat displ out dis2.dat beg 2 end 2
> >> >
> >> > 2)
> >> >>> If the only goal is to get two structures that look the least like
> each
> >> > other, one way is to calculate the 2D RMSD
> >> >
> >> > This is nice suggestion indeed. I was following some previous amber
> >> archive
> >> > mails to generate procupine plots which needs two extreme pdbs in
> >> > discussion it was not mentioned how one can get two extremes.
> >> >
> >> > best regards
> >> >
> >> >
> >> > On Wed, May 7, 2014 at 4:27 AM, Daniel Roe <daniel.r.roe.gmail.com>
> >> wrote:
> >> >
> >> >> On Tue, May 6, 2014 at 8:13 PM, newamber list <
> newamberlist.gmail.com>
> >> >> wrote:
> >> >> > runanalysis diagmatrix myCovar out evecs.dat vecs 15
> >> >> > readdata evecs.dat
> >> >> > modes displ out dis.dat name myCovar beg 1 end 3 :1-328.N
> >> >> ###
> >> >>
> >> >> The problem here is that you are trying to use 'myCovar' (which is a
> >> >> matrix) as your modes data set, which by default will be called
> >> >> 'evecs.dat' since you did not supply a name. Try using 'modes name
> >> >> evecs.dat ...'.
> >> >>
> >> >> > 2) Also how one can obtain two extreme configurations of system for
> >> whole
> >> >> > traj? Just by using lowest and highest rmsd with respect to average
> >> >> > structure or something one can do with PCA?
> >> >>
> >> >> If the only goal is to get two structures that look the least like
> >> >> each other, one way is to calculate the 2D RMSD and find the pair of
> >> >> frames with the largest RMSD. You will probably want to use the
> >> >> 'nosquare2d' option with standard data output to make searching
> >> >> easier, e.g.
> >> >>
> >> >> 2drms .CA out rms2d.dat
> >> >> datafile rms2d.dat nosquare2d
> >> >>
> >> >> Hope this helps,
> >> >>
> >> >> -Dan
> >> >>
> >> >> >
> >> >> > thanks
> >> >> > JIom
> >> >> >
> >> >> >
> >> >> >
> >> >> > On Tue, May 6, 2014 at 6:24 PM, Daniel Roe <daniel.r.roe.gmail.com
> >
> >> >> wrote:
> >> >> >
> >> >> >> Hi,
> >> >> >>
> >> >> >> On Mon, May 5, 2014 at 5:23 PM, newamber list <
> >> newamberlist.gmail.com>
> >> >> >> wrote:
> >> >> >> > 2) Also in many papers there are Principal component plots. If
> am
> >> not
> >> >> >> > wrong these are same obtained from 'projection modes' as shown
> >> below
> >> >> >> > (myproj.txt). Or its something else?
> >> >> >>
> >> >> >> The plots you refer to are actually histograms generated using the
> >> >> >> 'hist' command of the principal component projections obtained
> from
> >> >> >> the 'projection' command, see the bottom of the script in
> >> >> >>
> >> >> >>
> >> >>
> >>
> http://pubs.acs.org/doi/suppl/10.1021/ct400862k/suppl_file/ct400862k_si_001.pdf
> >> >> >> .
> >> >> >>
> >> >> >> > trajin 1trj.nc
> >> >> >> > trajin 2trj.nc
> >> >> >> > rms first :1-328.N
> >> >> >> > average Avg.rst7 ncrestart
> >> >> >> > createcrd crd1
> >> >> >> > run
> >> >> >> >
> >> >> >> > reference Avg.rst7.1 [avg]
> >> >> >> > crdaction crd1 rms ref [avg] :1-328.N
> >> >> >> > crdaction crd1 matrix covar :1-328.N name myCovar
> >> >> >> > runanalysis diagmatrix myCovar out evecs.dat vecs 15
> >> >> >> >
> >> >> >> > readdata evecs.dat
> >> >> >> > crdaction crd1 projection modes evecs.dat out myproj.txt beg 1
> end
> >> 3
> >> >> >> :1-328.N
> >> >> >>
> >> >> >> The last 'projection' command will create 3 data sets
> (corresponding
> >> >> >> to projections for PCs 1, 2, and 3) which you can then histogram,
> >> >> >> either with cpptraj or your favorite program. It will be probably
> be
> >> >> >> easier to histogram within cpptraj if you name the 'projection'
> data
> >> >> >> sets, e.g.:
> >> >> >>
> >> >> >> crdaction crd1 projection P1 modes evecs.dat out myproj.txt beg 1
> >> end 3
> >> >> >> :1-328.N
> >> >> >> runanalysis hist P1:1,*,*,*,100 out pca.hist.agr norm name P1-1
> >> >> >>
> >> >> >> etc. See the manual for more details on the 'hist' command (or
> >> >> >> alternatively the 'kde' command to use a kernel density estimator
> >> >> >> instead).
> >> >> >>
> >> >> >> Hope this helps,
> >> >> >>
> >> >> >> -Dan
> >> >> >>
> >> >> >> >
> >> >> >> > Thanks
> >> >> >> > _______________________________________________
> >> >> >> > AMBER mailing list
> >> >> >> > AMBER.ambermd.org
> >> >> >> > http://lists.ambermd.org/mailman/listinfo/amber
> >> >> >>
> >> >> >>
> >> >> >>
> >> >> >> --
> >> >> >> -------------------------
> >> >> >> 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) 585-6208 (Fax)
> >> >> >>
> >> >> >> _______________________________________________
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> >> >> >>
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> >> >>
> >> >>
> >> >>
> >> >> --
> >> >> -------------------------
> >> >> 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) 585-6208 (Fax)
> >> >>
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> >>
> >>
> >>
> >> --
> >> -------------------------
> >> 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) 585-6208 (Fax)
> >>
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>
>
>
> --
> -------------------------
> 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) 585-6208 (Fax)
>
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Received on Sun May 11 2014 - 12:30:02 PDT
