title: Local alignment of two-base encoded DNA sequence.
abstract: BACKGROUND
  DNA sequence comparison is based on optimal local alignment of two sequences using a similarity score. However, some new DNA sequencing technologies do not directly measure the base sequence, but rather an encoded form, such as the two-base encoding considered here. In order to compare such data to a reference sequence, the data must be decoded into sequence. The decoding is deterministic, but the possibility of measurement errors requires searching among all possible error modes and resulting alignments to achieve an optimal balance of fewer errors versus greater sequence similarity.
  
  
  RESULTS
  We present an extension of the standard dynamic programming method for local alignment, which simultaneously decodes the data and performs the alignment, maximizing a similarity score based on a weighted combination of errors and edits, and allowing an affine gap penalty. We also present simulations that demonstrate the performance characteristics of our two base encoded alignment method and contrast those with standard DNA sequence alignment under the same conditions.
  
  
  CONCLUSIONS
  The new local alignment algorithm for two-base encoded data has substantial power to properly detect and correct measurement errors while identifying underlying sequence variants, and facilitating genome re-sequencing efforts based on this form of sequence data.
authors.affiliation: Department of Computer Science, University of California Los Angeles, Los Angeles, California 90095, USA. nhomer@cs.ucla.edu
authors.forename: Nils
authors.initials: N
authors.lastname: Homer
authors.forename: Barry
authors.initials: B
authors.lastname: Merriman
authors.forename: Stanley F
authors.initials: SF
authors.lastname: Nelson
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D004247:DNA / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D004247:DNA