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ΔCC<sub>1/2</sub> is a quantity, that detects datasets/frames, that are non-isomorphous. As described in [https://scripts.iucr.org/cgi-bin/paper?zw5005 Assmann and Diederichs (2016)], ΔCC<sub>1/2</sub> is calculated with the σ-τ method. This method is a way to calculate the Pearson correlation coefficient for the special case of two sets of values (intensities) that randomly deviate from their true values, but is not influenced by a random number sequence as shown in [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3457925/ Karplus and Diederichs (2012)]. For the σ-τ method CC<sub>1/2</sub> is calculated for all datasets/frames, which will be called CC<sub>1/2_overall</sub> and CC<sub>1/2</sub> is calculated for all datasets/frames except for one dataset i, which is omitted from calculations and denoted as CC<sub>1/2_i</sub>. The difference of the two quantities is ΔCC<sub>1/2</sub>. | |||
: <math>\Delta CC_{1/2}= CC_{1/2 overall}-CC_{1/2 i} </math> | : <math>\Delta CC_{1/2}= CC_{1/2 overall}-CC_{1/2 i} </math> | ||
If | If ΔCC<sub>1/2_</sub> is > 0 -CC<sub>1/2_overall</sub> is bigger than CC<sub>1/2_i</sub>- that means if omitting dataset i from calculations, a lower CC<sub>1/2</sub> results, which is why we want to keep it. Thus it is improving the whole merged dataset. If Δ CC<sub>1/2</sub> is < 0, -CC<sub>1/2_overall</sub> is smaller than CC<sub>1/2_i</sub> - that means that by omitting dataset i from calculations a higher CC<sub>1/2</sub> results, which is why we want to exclude it from calculations, because it is impairing the whole merged dataset. | ||
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== Program == | == Program == |