For example, in a mammalian genome we saw this region with no binding
1182662 0.014 0.007 0.518 0.096 1182692 0.013 0.007 0.506 0.090 1182722 0.013 0.007 0.524 0.091 1182752 0.013 0.007 0.552 0.093 1182782 0.013 0.007 0.566 0.092 1182812 0.013 0.007 0.553 0.086 1182842 0.013 0.007 0.496 0.080 1182872 0.013 0.007 0.453 0.073 1182902 0.013 0.007 0.435 0.071 1182932 0.013 0.007 0.422 0.069
and this region with binding
37688946 0.016 0.009 1.411 0.376 37688976 0.016 0.009 1.916 0.568 37689006 0.015 0.008 2.707 0.820 37689036 0.015 0.008 3.700 1.007 37689066 0.029 0.021 4.949 1.222 37689096 0.209 0.155 6.103 1.535 37689126 0.540 0.232 6.909 1.783 37689156 0.626 0.216 7.629 2.156 37689186 0.587 0.225 8.380 2.781 37689216 0.541 0.232 9.194 3.706 37689246 0.467 0.234 9.709 4.906 37689276 0.346 0.213 9.324 5.955 37689306 0.151 0.119 7.400 5.789 37689336 0.094 0.077 5.198 4.459 37689366 0.061 0.050 3.542 3.510 37689396 0.043 0.034 2.685 2.415 37689426 0.033 0.025 2.176 1.583
In general, you should ignore the strength output unless the posterior probability of binding is above background (.1 is a safe value in most cases, though in many cases you can use a cutoff as low as .05). Wide areas of elevated posterior indicate either multiple binding events or uncertainty as to the exact binding location.
To convert JBD's output to a discrete set of binding events, you can run jbd2bindingevents.pl on an output file:
jbd2bindingevents.pl < sc_gcn4.1.1.jbd > sc_gcn4.1.1.events
This produces three tab delimited columns:
We use a threshold on both the maximum posterior probability and the size. The maximum posterior probability roughly corresponds to confidence: how well does the data fit the model of binding at the best position. The size roughly corresponds to the enrichment ratio: how strong is the binding here.