DIALS analysis report

The inverse scale factor g, for a given reflection i, is defined as the product
of the individual model components.
For the physical scaling model, up to three terms are defined:
smoothly-varying scaling term Ci,
isotropic radiation damage term Ri = exp( Bi / (2 * di * di) ),
absorption surface correction Si,
The scaled intensity is therefore given by Ii / gi, where
gi = Ci * Ri * Si

The absorption correction uses a set of spherical harmonic functions as the
basis of a smoothly varying absorption correction as a function of phi and
theta (relative to the crystal reference frame). The correction is given by:
S(s0, s1) = 1 + sum [Clm * (Ylm(s1) + Ylm(s0)) /2]
where each Ylm is a spherical harmonic and each Clm is a model parameter.
The parameters (Clm values) are shown in the 'Absorption correction surface
parameters' plot. For each l=1,2,...,lmax, there are 2l+1 m-values
from -l, -l+1,...,l+1,l, shown in the plot from left to right for each l.
s0 and s1 are the incoming and scattered beam vectors.

The absorption correction uses a set of spherical harmonic functions as the
basis of a smoothly varying absorption correction as a function of phi and
theta (relative to the crystal reference frame). The correction is given by:
S(s0, s1) = 1 + sum [Clm * (Ylm(s1) + Ylm(s0)) /2]
where each Ylm is a spherical harmonic and each Clm is a model parameter.
The parameters (Clm values) are shown in the 'Absorption correction surface
parameters' plot. For each l=1,2,...,lmax, there are 2l+1 m-values
from -l, -l+1,...,l+1,l, shown in the plot from left to right for each l.
s0 and s1 are the incoming and scattered beam vectors.

    The correlation coefficients, CC½, between random half-datasets. A correlation
    coefficient of +1 indicates good correlation, and 0 indicates no correlation.
    CC½ is typically close to 1 at low resolution, falling off to close to zero at
    higher resolution. A typical resolution cutoff based on CC½ is around 0.3-0.5.

    [1] Karplus, P. A., & Diederichs, K. (2012). Science, 336(6084), 1030-1033.
        https://doi.org/10.1126/science.1218231
    [2] Diederichs, K., & Karplus, P. A. (2013). Acta Cryst D, 69(7), 1215-1222.
        https://doi.org/10.1107/S0907444913001121
    [3] Evans, P. R., & Murshudov, G. N. (2013). Acta Cryst D, 69(7), 1204-1214.
        https://doi.org/10.1107/S0907444913000061
    

This plot shows the distribution of I/σ(I) as a function of I, which can
give indication of the errors within the dataset. The I/σ(I) asymptotic
limit can be seen at the plateau in the top-right of the plot, if the measured
data are strong enough.

[1] Diederichs, K. (2010). Acta Cryst. D, 66(6), 733-740.
https://doi.org/10.1107/S0907444910014836

    This plot shows the normalised anomalous differences, sorted in order and
    plotted against the expected order based on a normal distribution model.
    A true normal distribution of deviations would give the straight line indicated.

    [1] P. L. Howell and G. D. Smith, J. Appl. Cryst. (1992). 25, 81-86
    https://doi.org/10.1107/S0021889891010385
    [2] P. Evans, Acta Cryst. (2006). D62, 72-82
    https://doi.org/10.1107/S0907444905036693
    

This plot shows the correlation of the anomalous differences for the data divided
into two half sets. For each reflection, the I+ and I- observations are divided
into two sets, and two differences are calculated; Delta I1 = I+(1) - I-(1),
Delta I2 = I+(2) - I-(2). Perfect data would therefore have all points along
the diagonal, in reality an elliptical distribution is seen in the presence of
anomalous signal, or a spherical distribution for data with no anomalous signal.

[1] P. Evans, Acta Cryst. (2006). D62, 72-82
https://doi.org/10.1107/S0907444905036693

This plot shows the significance of the anomalous signal, as shown in the
anomalous scatter plot, by calculating the ratio of the width of the signal along
the diagonal (a measure of the anomalous signal) over the width of the signal
perpendicular to the diagonal (a measure of the error).

[1] P. Evans, Acta Cryst. (2006). D62, 72-82
https://doi.org/10.1107/S0907444905036693