At the risk of deafness from bees in bonnet (not to mention flogging
dead horses) ...
... the rms value of a "Fobs"-type map which represents the actual
structure (eg 2mFo - DFc) is _not_ an assessment of the "noise" level
of the map.
The rms value of a perfect map of this type is function of the
sharpness of protein features (which depends on the resolution & the B-
factors) and the solvent content (imagine the different rms levels of
the same molecule density placed in a cell with 40% solvent compared
to one with 80% solvent), and is not much related to the error.
The rms value is useful in ranking peaks in a difference map, but
even then if you imagine a near perfect difference map (we can dream),
close to zero density everywhere, there will still be peaks > 3 rms,
but they are not necessarily significant.
(yawn)
Phil
On 30 Jul 2008, at 12:58, P K wrote:
> Thank you, Paul and Hidong, for your explanations. Here is another
> way of looking at it (kindly provided by Ronald Stenkamp).
>
> ===
> Think of the electron density as a 3-dimensional function with an
> average value of 0.0 (This is true if you have not included an F000
> reflection, and it's true of difference electron density maps).
>
> You can take that function and calculate its rms value.
>
> That would be its rms deviation from the average, and you can
> convert that to an estimated standard deviation (or simply call it
> because of the large number of data points in this function). Sigma
> is the standard deviation, and it's a quantitative way of assessing
> the noise level of the map.
>
> So you can then ask the following question for any peak in the map:
> Is this peak significant or not?
>
> One way to decide on that is to ask how much larger is this peak
> than the estimated standard deviation of the map?
>
> High peaks, because they are much above the noise, are more
> significant than are the low peaks. And high peaks are those that
> will be shown on your graphics screen as you increase the sigma
> level of the contours.
> ===
>
>
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