Physical mapping with automatic capture of hybridization data

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Abstract
Motivation: Contig maps are a type of physical map that show the native order of a set of overlapping genomic clones. Overlaps between clones can be detected by finding common sequences using a number of experimental protocols including hybridization of probes. All current mapping algorithms of which we are aware require that hybridizations be scored using a fixed number of discrete values (typically 0/1 or high/medium/low). When hybridization data is captured automatically using digital equipment, this provides the opportunity for hybridization intensities to be used in map construction. More fine-grained distinctions in the levels of hybridization may be exploited by algorithms to generate more accurate physical maps. Results: We describe an approach to creating contig maps that uses measured hybridization intensities instead of data scored with a fixed number of discrete values. We describe and compare four algorithms for creating physical maps with hybridization intensities. Simulations using measured intensities sampled from actual data on Aspergillus nidulans indicate that using hybridization intensities rather than data that is automatically scored with respect to threshold values may yield more accurate physical maps. Availability: All software programs described in this paper may be obtained by contacting the authors. Contact: suchi@cs.uga.edu

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