A computationally novel way to place new markers onto genetic maps

We study the problem of extending genetic linkage maps to include a large number of new markers. We note that this problem should be addressed by placing new markers into the breakpoint-induced bins of the mapping population, rather than by attempting to infer marker order and distance from recombination fractions among closely-placed markers, which are the approaches of current software. Based on this observation, we have constructed a new approach for the placement of new markers onto framework maps which is extremely fast and highly accurate, even when executed on small-sized mapping samples. Further, our approach provides an estimate of the error of the placements for new markers, so investigators will know how precise a new marker’s placement is expected to be. Unlike existing methods, our methods scale well as the number of new markers increases. We have tested these methods using both simulations and real biological data, and verified that both the placement of new markers and the estimation of the errors are precise. ∗ [email protected]. Department of Computer Science, Cornell University, Ithaca, NY 14853. Research supported by an NSF Graduate Research Fellowship, NSF grants CCR-970029, DMS-9805602 and DBI-98-72617, ONR grant N0014-96-1-00500, and the UPS Foundation. † [email protected]. USDA-ARS Center for Bioinformatics and Comparative Genomics, Cornell University,