From: Ryan McGreevy (ryanmcgreevy_at_ks.uiuc.edu)
Date: Wed May 24 2017 - 10:03:52 CDT

Timeline wasn't really designed to give a per-residue cross correlation
because (a) calculating the correlation for each residue for an entire
trajectory is very computationally heavy, even with the fast algorithm
Timeline uses and (b) most cryo-em maps are too low resolution for
per-residue calculations to make sense.

If you really want to do this though, you can write a fairly simple script
using the "mdffi cc" command. "mdffi" (note the 'i' at the end) is the
newer, faster algorithm that both Timeline and "mdff check" uses, versus
the older, slower "mdff ccc" command (though mdff ccc too will be changed
in the future, once all the bugs are worked out). Using this, you can just
calculate the mdffi cc for each residue you want in a tcl loop. I would
recommend only doing this for a single frame, however, and not an entire
trajectory if you have one.

On Wed, May 24, 2017 at 9:42 AM Karol KASZUBA <karol.kaszuba_at_ist.ac.at>
wrote:

> Hi Ryan,
>
> Thank you for your prompt reply.
>
> This is cryo-em model and in certain places there is no density at all,
> which would explain these low negative values.
>
> (1) Actually, I played with treshold a bit and now the values are quite
> nice, between 0.5-0.78.
> The value of treshold corresponds to the sigma values I use. So, it
> looks good now.
>
> (2) I also found that Timeline cc gives a much more reasonable score than
> mdff ccc.
>
> I played quite a lot with selection in Timeline. Can you tell me what
> would be the proper selection to get a per-residue score for a given
> segment of residues. For example, when I try {segname PRT1 and resid 1 to
> 29} it returns one number, most likely treating selection between {} as one
> segment. However, what I need is per-residue score.
> I have a big structure, so typing {resid 1} {resid 2} and so on will not
> work for me.
>
> thank you very much
>
>
>
>
> ------------------------------
> *From:* Ryan McGreevy [ryanmcgreevy_at_ks.uiuc.edu]
> *Sent:* Wednesday, May 24, 2017 4:16 PM
> *To:* Karol KASZUBA; vmd-l_at_ks.uiuc.edu
> *Subject:* Re: vmd-l: MDFF time line ccc score
>
> (1) In general those values are pretty low. Having a high of .35 is not
> very good. The extremely low negative values are most likely due to pieces
> of the structure that are sticking out of the map significantly, where
> correlation is undefined. You could also try using the "threshold" option
> in the Timeline cross correlation parameters (try 0.1 for example) which
> will remove some of the excess noise around your structure from the
> calculation. Is your structure that you are analyzing the result of a
> fitting, like MDFF? Without actually seeing the map and model it is hard to
> say anything more concrete.
>
> (2) It is okay that Timeline and mdff ccc do not give exactly the same
> results. First, if you ran Timeline with default options, the correlations
> are calculated on sections of contiguous secondary structure, not
> per-residue, so the CC's are not being calculated on exactly the same
> parts. Second, the algorithms used by the Timeline and mdff ccc are not
> exactly the same, so there will be small discrepancies, but shouldn't be
> more than a few hundredth.
>
> On Wed, May 24, 2017 at 2:50 AM Karol KASZUBA <karol.kaszuba_at_ist.ac.at>
> wrote:
>
>> Hi,
>>
>> I am trying to calculate the cross-correlation score between my map and
>> a model. The map is in .mrc format.
>>
>> (1) At first I used time line plugin and "calculate cc" option.
>> So, I got the scores. They make sense, but what I am worried is the
>> scale: it starts from -100 and finishes at 0.35. Is it normal?
>>
>> I would expect a score from 0 to 1, where low values would correspond to
>> poor density fit, while higher (positive) values would denote a good match.
>>
>> (2) I also calculated cc using "mdff ccc" command in tcl console. I just
>> choose one residue to see whether the cc score calculated in time line
>> and from command line. will be the same. These were not.
>>
>>
>> Please let me know what do you think
>> thanks
>> Karol
>>
>>