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. 2017 Jul 19;15:388–395. doi: 10.1016/j.csbj.2017.07.001

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© 2017 The Authors

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Fig. 2 — Performance of MultiRes on HCV datasets under power law distributions of viral haplotypes with respect to count of k-mer. 35-mer multiplicity plots for HCV1P and HCV2P datasets are shown. x-axis indicates the number of times a 35-mer was observed while y-axis indicates the number of 35-mers at a count. (a) The predicted true 35-mers from MultiRes (HCV1P red, HCV2P pink) compared to the uncorrected data (HCV1P blue,HCV2P green), and (b) The true positive rare variants 35-mers from MultiRes (HCV1P red, HCV2P pink) versus the ground truth 35-mers (HCV1P red, HCV2P pink). MultiRes predicts rare variants k-mers at all counts greater than 3, with its accuracy improving as counts of k-mer increases.