Fwd: [gmx-users] Eigenvector and eigenvalues
Ankita naithani
ankitanaithani at gmail.com
Sat Jun 8 13:06:08 CEST 2013
Hi Tsjerk,
[I am reposting it since my previous attachment was unable to proceed I
guess]
Thank you for the reply. I am sorry but I don't have the snapshots with me
as my system was formatted and I lost that information. However, I
performed PCA again on Calpha atoms and this time my matrix is 5976X5976
wherein 1992 are my total number of calpha atoms. So, yes indeed I did
something foolish in the previous case to have got that result. However, I
will try to look at it and find my mistake so as to not repeat it again.
I would be really grateful if you could help me with my another naive
query. I wanted to see the movie of first few eigenvectors as individual
and also separately. I know I can extract that with the help of g_anaeig
but as I did PCA on only calpha atoms, all I get in the projection of first
eigenvector is the calpha dots. Is there any way, I can visualise the
projection of whole protein on that particular eigenvector?
Secondly, if I want to see the projection along first 10 eigenvectors and
last 10 eigenvectors (slow modes and fast modes), how could I proceed
because when I choose -first 1 -last 10, it gives me individual pdb files
corresponding to the eigenvectors.
Third, as can be judged by my absolute naivety, I did a 2d projection on PC
1 and PC 2. I can visualise that plot in grace as a 2d plot. An example
file is appended herein. I know each dot might correspond to a particular
conformation in the trajectory but I really have no idea as to how to
interpret the results and draw conclusions from these 2d plots and also 3d
pdb projections. Could you please guide me in the right direction to
understand these 2d plots and infer the significant results?
Kind regards,
Ankita
On Thu, Jun 6, 2013 at 2:49 PM, Tsjerk Wassenaar <tsjerkw at gmail.com> wrote:
>
>> Hi Ankita,
>>
>> Please provide the commands you've run and the screen output from g_covar.
>>
>> Cheers,
>>
>> Tsjerk
>>
>>
>>
>> On Thu, Jun 6, 2013 at 3:44 PM, Ankita naithani <ankitanaithani at gmail.com
>> >wrote:
>>
>> > Hi,
>> >
>> > I wanted to know about the eigenvectors and eigenvalues. I recently
>> > performed the principal component analysis (only the backbone into
>> > consideration) on a trajectory of 2000 residues. I obtained 15641
>> > eigenvectors and 17928 eigenvalues. There is a difference in the number,
>> > which I am not quite sure off (perhaps that has to do with eigenvalue
>> for
>> > each eigenvector, and the eigenvector has 3 co-ordinates x,y,z. I know I
>> > may be wrong completely but since there are 15641 eigenvectors, then
>> > shouldn't there by only 15641 eigenvalues for those eigenvectors)
>> >
>> > My second problem lies that I am trying to extract information or say
>> RMSF
>> > values for the first 10 eigenvectors (10 slowest modes) and the last 10
>> > eigenvectors (fastest modes) and there I face segmentation fault. I can
>> get
>> > information on the first 10 but when I try last 10 with the command as
>> > follows:
>> >
>> > g_anaeig -v eigenvec.trr -eig eigenval.xvg -rmsf eig_rmsf.xvg -first
>> 15631
>> >
>> > [where -first should have the starting eigenvector ]
>> >
>> > (I choose, 15631 since I want the plot for last 10 but I get
>> segmentation
>> > fault, which is also to do with the fact that the eigenval.xvg has 17928
>> > values. This number doesn't match and so, maybe the plot is from
>> > 15631-17928). This has further confused me about the slowest and fastest
>> > modes (and somehow I do need information on the first 10 slowest modes
>> and
>> > 10 fastest modes). In a broad way, the slowest modes would be the ones
>> with
>> > high eigenvalues say, first 10 eigenvectors in eigenval.xvg would give
>> the
>> > slowest 10 modes and the last 10 in eigenval.xvg should give the
>> fastest 10
>> > modes.
>> >
>> > Here, again I feel quite confused because eigenval.xvg has 17928 entries
>> > and in the legend, it says that x axis is the eigenvector index and y
>> axis
>> > is eigenvalue index so it leaves me quite perplexed about the problem.
>> >
>> > I am sorry for this extremely long and confusing post, but any help in
>> this
>> > regard would be really beneficial.
>> >
>> >
>> > Kind regards,
>> >
>> > Ankita
>> >
>> > --
>> > Ankita Naithani
>> > --
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>>
>>
>>
>> --
>> Tsjerk A. Wassenaar, Ph.D.
>> --
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>
>
>
> --
> Ankita Naithani
>
--
Ankita Naithani
--
Ankita Naithani
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