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Fig. 2 | Genome Biology

Fig. 2

From: Chromatin segmentation based on a probabilistic model for read counts explains a large portion of the epigenome

Fig. 2

Assembly gap prediction. Chromatin states can be used as binary classifiers for detecting assembly gaps. Given a state, the true positives are the bins annotated with that state and where the reference sequence is not known (so no reads can be mapped). The specificity, or precision, is the number of true positives divided by the number of bins annotated with the state, the sensitivity is the number of true positives divided by the number of bins corresponding to assembly gaps. The state which gives maximum precision has been chosen

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