. Dense genetic linkage maps enable the identification of causative genes for genetic disease. Using these maps to genetically localize even one disorder on the genome requires hundreds of thousands of genotyping experiments. This genotyping process has been automated through the use of PCR-based microsatellite markers, automated DNA sequencers, robotic handling, and computer analysis. However, the microsatellite markers produce an intrinsic PCR stutter artifact that has thus far precluded full genotyping automation. Recently computational methods have been developed that overcome this key molecular biology bottleneck. The applicants software system automatically transforms DNA sequencer data files into genotypes. Limited empirical testing of such software system on DNA sequencer data has produced genotypes at a low error rate. These initial results suggest that further testing and validation may establish the feasibility of this computational approach. If ultimately successful, the methods described may help advance the accurate and rapid localization of genes within the human genome. This application focuses on determining the feasibility of (1) automated microsatellite genotyping with low error on data from automated DNA sequencers and (2) automated microsatellite genotyping using pooled DNA material.