Genetic mapping of loci affecting complex phenotypes in human and other organisms is presently being conducted on a very large scale, using either microsatellite or single nucleotide polymorphism (SNP) markers and by partly automated methods. A critical step in this process is the conversion of the instrument output into genotypes, both a time-consuming and error prone procedure. Errors made during this calling of genotypes will dramatically reduce the ability to map the location of loci underlying a phenotype. Accurate methods for automatic genotype calling are therefore important. Here, we describe novel algorithms for automatic calling of microsatellite genotypes using parametric pattern recognition. The analysis of microsatellite data is complicated both by the occurrence of stutter bands, which arise from Taq polymerase misreading the number of repeats, and additional bands derived form the non-template dependent addition of a nucleotide to the 3' end of the PCR products. These problems, together with the fact that the lengths of two alleles in a heterozygous individual may differ by only two nucleotides, complicate the development of an automated process. The novel algorithms markedly reduce the need for manual editing and the frequency of miscalls, and compares very favourably with commercially available software for automatic microsatellite genotyping.