BAC Overlap Identification Based on Bit-Vectors

Authors:
Jens-Uwe Krause;Jürgen Kleffe
Affiliations:
Institute for Molecularbiology and Bioinformatics, Charité, Berlin, Germany;Institute for Molecularbiology and Bioinformatics, Charité, Berlin, Germany
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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Abstract

There is no software that accurately calculates the overlap of two BACs fast enough for application to thousands of cases in turn. The problems include unacceptably low speed of dynamic programming algorithms for sequences of the considered size and failure of the faster local alignment methods to identify complete sequence overlaps. Lower sequence quality at both BAC ends and internal difference blocks, being small enough to not significantly increase relative error rates but large enough to terminate local alignments, cause output of multiple overlapping local matches which do not extend to both sequence ends. Based on Myers' bit-vector algorithm for fast edit distance calculation, we developed the program BACOLAP, that identifies overlapping BACs just as sensitive as global dynamic programming alignment and as fast as local heuristic alignment.