Refinement of optical map assemblies

Anton Valouev, Yu Zhang, David C. Schwartz, Michael S. Waterman

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Motivation: Genomic mutations and variations provide insightful information about the functionality of sequence elements and their association with human diseases. Traditionally, variations are identified through analysis of short DNA sequences, usually shorter than 1000 bp per fragment. Optical maps provide both faster and more cost-efficient means for detecting such differences, because a single map can span over 1 million bp. Optical maps are assembled to cover the whole genome, and the accuracy of assembly is critical. Results: We present a computationally efficient model-based method for improving quality of such assemblies. Our method provides very high accuracy even with moderate coverage (<20 ×). We utilize a hidden Markov model to represent the consensus map and use the expectation-Maximization algorithm to drive the refinement process. We also provide quality scores to assess the quality of the finished map.

Original languageEnglish (US)
Pages (from-to)1217-1224
Number of pages8
Issue number10
StatePublished - May 15 2006

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


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