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Figure 3 | BMC Bioinformatics

Figure 3

From: Methodology and software to detect viral integration site hot-spots

Figure 3

Comparison of VIS clustering among data sets. We developed two methods to describe the extent of VIS clustering. The first method 'maximum %' is simply the maximum bin's z-score divided by the total number of VIS in the data set, 100max ( X ) i = 1 n C i . Data sets with a maximum % > 8 indicate a high degree of clustering. The second method 'BCP posterior probability' is calculated after running the Bayesian change-point analysis, and is simply one minus the average of the posterior probabilities of a change point occurring at each bin, 1- P ¯ . BCP posterior probabilities > 0.98 indicate a high degree of clustering. Both methods indicate that the CGD data exhibits a high degree of clustering with a maximum % and BCP posterior probabilities of 11.98 and 0.999, respectively, in comparison to the other data sets which ranged from 0.5-1.48 and 0.9356-0.9361, respectively.

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