Alignment of Optical Maps

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 likelihoods. The size error model is derived through the application of Central Limit Theorem and validated by residual plots collected from real data. Missing cuts and false cuts are modeled as Bernoulli and Poisson events, respectively, as suggested by previous studies. Likelihoods are used to derive an alignment score through calculation of likelihood ratios for a certain hypothesis test. This allows us to achieve maximal descriminative power for the alignment score. Our scoring method is naturally embedded within a well known DP framework for finding optimal alignments. Key words: optical mapping, alignment score, restriction mapping, dynamic programming, likelihood ratio.

• Type: Conference
• Year: 2005
• Where: RECOMB
• Authors: Anton Valouev, Lei Li, Yu-Chi Liu, David C. Schwartz, Yi Yang, Yu Zhang, Michael S. Waterman
• Keywords: Alignment Score, Central Limit Theorem, Computational Biology, RECOMB 2005, Size Error Model