SEA: Difference between revisions
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[prompt]$ sea-fit model.out | [prompt]$ sea-fit model.out | ||
This generates the file model.out.distfit, containing the values for the best fit of the background distribution to a normal and an extreme value distribution. From this distribution, we need to select the optimal cutoff and then use it to get the fit file. | This generates the file model.out.distfit, containing the values for the best fit of the background distribution to a normal and an extreme value distribution. From this distribution, we need to select the optimal cutoff (in general we look for the similarity value that better fits to EVD) and then use it to get the fit file. | ||
[prompt]$ sea-fit -c cutoff model.out | [prompt]$ sea-fit -c cutoff model.out | ||
Revision as of 04:34, 10 October 2012
SEA, the similarity ensemble approach. sea.docking.org
How to generate a model to run SEA
We need the files: reference.smi ; reference.set ; reference.fp
First we need to generate the background Z-score distribution:
[prompt]$ sea-background reference.set.gz
This generated the file model.out
Then we need to fit data the data from this background model and build a fit parameter file:
[prompt]$ sea-fit model.out
This generates the file model.out.distfit, containing the values for the best fit of the background distribution to a normal and an extreme value distribution. From this distribution, we need to select the optimal cutoff (in general we look for the similarity value that better fits to EVD) and then use it to get the fit file.
[prompt]$ sea-fit -c cutoff model.out