On Monday 08 September 2008 12:30:29 Phoebe Rice wrote:
Dear Experts,
At the risk of exposing excess ignorance, truncate makes me
very nervous because I don't quite get exactly what it is
doing with my data and what its assumptions are.
From the documentation:
========================================================
... the "truncate" procedure (keyword TRUNCATE YES, the
default) calculates a best estimate of F from I, sd(I), and
the distribution of intensities in resolution shells (see
below). This has the effect of forcing all negative
observations to be positive, and inflating the weakest
reflections (less than about 3 sd), because an observation
significantly smaller than the average intensity is likely
to be underestimated.
=========================================================
But is it really true, with data from nice modern detectors,
that the weaklings are underestimated?
It isn't really an issue of the detector per se, although in
principle you could worry about non-linear response to the
input rate of arriving photons.
In practice the issue, now as it was in 1977 (French&Wilson),
arises from the background estimation, profile fitting, and
rescaling that are applied to the individual pixel contents
before they are bundled up into a nice "Iobs".
I will try to restate the original French & Wilson argument,
avoiding the terminology of maximum likelihood and Bayesian statistics.
1) We know the true intensity cannot be negative.
2) The existence of Iobs<0 reflections in the data set means
that whatever we are doing is producing some values of
Iobs that are too low.
3) Assuming that all weak-ish reflections are being processed
equivalently, then whatever we doing wrong for reflections with
Iobs near zero on the negative side surely is also going wrong
for their neighbors that happen to be near Iobs=0 on the positive
side.
4) So if we "correct" the values of Iobs that went negative, for
consistency we should also correct the values that are nearly
the same but didn't quite tip over into the negative range.
Do I really want to inflate them?
Yes.
Exactly what assumptions is it making about the expected
distributions?
Primarily that
1) The histogram of true Iobs is smooth
2) No true Iobs are negative
How compatible are those assumptions with serious anisotropy
and the wierd Wilson plots that nucleic acids give?
Not relevant
Note the original 1978 French and Wilson paper says:
"It is nevertheless important to validate this agreement for
each set of data independently, as the presence of atoms in
special positions or the existence of noncrystallographic
elements of symmetry (or pseudosymmetry) may abrogate the
application of these prior beliefs for some crystal
structures."
It is true that such things matter when you get down to the
nitty-gritty details of what to use as the "expected distribution".
But *all* plausible expected distributions will be non-negative
and smooth.
Please help truncate my ignorance ...
Phoebe
==========================================================
Phoebe A. Rice
Assoc. Prof., Dept. of Biochemistry & Molecular Biology
The University of Chicago
phone 773 834 1723
http://bmb.bsd.uchicago.edu/Faculty_and_Research/01_Faculty/01_Faculty_Alphabetically.php?faculty_id=123
RNA is really nifty
DNA is over fifty
We have put them
both in one book
Please do take a
really good look
http://www.rsc.org/shop/books/2008/9780854042722.asp
--
Ethan A Merritt
Biomolecular Structure Center
University of Washington, Seattle 98195-7742
