Analysis of linkage data has typically been carried out assuming genot
yping errors are absent. Recent studies have shown, however, that the
impact of ignoring genotyping errors can be great, especially in dense
marker maps [Buetow, Am J Hum Genet 1991;49:985-994; Lincoln and Land
er, Genomics 1992;14:604-610]. Because most organisms exhibit positive
chiasma interference, we use the chi(2) model [Foss et al., Genetics
1993;144:681-691] to examine the role interference plays in the estima
tion of genetic distance in the presence of genotyping errors. For sim
plicity, we confine our analyses to samples of 1,000 fully informative
gametes. Our results support previous findings that ignoring errors i
nflates distance estimates. The larger the error rate, the greater the
inflation. For a given error rate, the relative error in estimated ge
netic distance is greatest when interference is known to be weak or ab
sent. An approximation to relative error which quantifies the relation
to distance, error rate, and interference is provided. Robustness of
estimation to error misspecification is also investigated. When the as
sumed error rate is too low, distance is overestimated while interfere
nce is underestimated. The situation is reversed when too large an err
or rate is assumed (interference is overestimated, and distance undere
stimated). Unfortunately, the joint estimation of distance and interfe
rence is not very robust to error misspecification.