# [gmx-users] Fwd: Related to PCA

João Henriques joao.m.a.henriques at gmail.com
Sat Oct 7 21:55:31 CEST 2017

Hello!

>From your email it's difficult to understand whether you're familiar with
the analysis and just seek specialized help on a particular interpretation,
or whether you're completely new to PCA and want an overall explanation of
it. In case of the latter, I suggest literature research. To understand
PCA, you need to have an idea of what eigenvector-based multivariate
analyses are and what each eigenvector or principal component of your
system is. This is often non-trivial and I strongly suggest to study the
topic a bit before attempting the analysis for the sake of having a free
energy landscape that you then don't know how to interpret.

However, if you're familiar with the subject and merely want help
visualizing how the projection of the first 2 PCs roughly describes the
(majority of the) variance on your system, here is an old email by Tsjerk
Wassenaar. This has to be one of the best/funniest explanations about
eigenvectors and PCA in the history of gmx-users:

"""
Hi Brett,

Let's say you're sitting at your _desk_ writing that paper with a deadline
yesterday and you put a quick _meal_ next to you, wondering why on _earth_
you keep up with this. Your hands are moving between the meal and the
keyboard. You notice that the average position of your hands is somewhere
between the two and mark the mean position on your desk. Then you draw a
line through it that corresponds to the major extent of the motion of your
hands, and write 'eigenvector 1' along it. You add a line through the
average position, perfectly perpendicular to the first, and write
'eigenvector 2' along it. Now you can project every position of your hands
onto your desk, giving it an 'eigenvector 1' coordinate (or score) and an
'eigenvector 2' coordinate (or score). You notice that it's only part of
the total motion, as you neglect the height, which will be a third line,
perpendicular to the desk.

You can look at it a bit differently and say that your desk is the subspace
of your real space, spanned by the two perpendicular vectors, which
together describe most of your hand's motion.

I hope this makes some sense :)

Cheers,

Tsjerk
"""

Here is the source. Check the original post and the subsequent answers by
Tsjerk and António Baptista.

https://mailman-1.sys.kth.se/pipermail/gromacs.org_gmx-users/2015-March/095916.html

Cheers,
João

On Sat, Oct 7, 2017 at 6:02 PM, Nikhil Maroli <scinikhil at gmail.com> wrote:

> Hi,
>
> By getting the coordinates you can find the corresponding structure. I can
> send some articles or materials to understand and analyse PCA and FEL,
> Kindly drop a mail to me.
> --
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