We introduce a new scoring method for calculation of alignments of optical maps. Missing cuts, false cuts and sizing errors present in optical maps are addressed by our alignment score through calculation of corresponding likelihood ratios. The Sizingerror model is derived through the application of CLT and validated by residual plots collected from real data. Missing cuts and false cuts are modeled as Bernoulli and Poisson events respectively. This probabilistic framework is used to derive an alignment score through calculation of likelihood ratio. Consequently, this allows to achieve maximal descriminative power for alignment calculation. The proposed scoring method is naturally embedded within a well known DP framework for finding optimal alignments.
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