Contig selection in physical mapping

In physical mapping, one orders a set of genetic landmarks or a library of cloned fragments of DNA according to their position in the genome. Our appr oach to physical mapping divides the problem into smaller and easier subpro blems by partitioning the probe set into independent parts (probe contigs), For this purpose we introduce a new distance function between probes, the averaged rank distance (ARD) derived from bootstrap resampling of the raw d ata. The ARD measures the pairwise distances of probes within a contig and smoothes the distances of probes across different contigs. It shows distinc t jumps at contig borders. This makes it appropriate for contig selection b y clustering We have designed a physical mapping algorithm that makes use o f these observations and seems to be particularly well suited to the deline ation of reliable contigs. We evaluated our method on data sets from two ph ysical mapping projects. On data from the recently sequenced bacterium Xyle lla fastidiosa, the probe contig set produced by the new method was evaluat ed using the probe order derived from the sequence information. Our approac h yielded a basically correct contig set. On this data we also compared our method to an approach which uses the number of supporting clones to determ ine contigs. Our map is much more accurate. In comparison to a physical map of Pasteurella haemolytica that was computed using simulated annealing, th e newly computed map is considerably cleaner. The results of our method hav e already proven helpful for the design of experiments aimed at further imp roving the quality of a map.