Misspecification of relationships and of genotype data can cause problems in linkage analyses based on genome-scan data. Previous reports have focused on pairwise relationships and a simple error model. This article considers the increased information available from the joint analysis of trios of individuals, integrating this analysis with an error model that allows for the most common genotyping errors. Given observed marker phenotypes in a genome scan, computational methods are outlined both for likelihoods of relationships and for the posterior probabilities of underlying genotypes. The methods are applied to examples from two real data sets: one has been previously well analyzed, and, hence, Mendelian inconsistencies have been removed; the other typifies the pedigree and genotype errors encountered in the initial analyses of a study. It is demonstrated that the coupling of relationship inference and error detection is quite effective, that the error model is computationally practical, and that data on a third relative can often clarify relationships.