Population stratification in Argentina strongly influences likelihood ratio estimates in paternity testing as revealed by a simulation-based approach.

A simulation-based analysis was carried out to investigate the potential effects of population substructure in paternity testing in Argentina. The study was performed by evaluating paternity indexes (PI) calculated from different simulated pedigree scenarios and using 15 autosomal short tandem repeats (STRs) from eight Argentinean databases. The results show important statistically significant differences between PI values depending on the dataset employed. These differences are more dramatic when considering Native American versus urban populations. This study also indicates that the use of Fst to correct for the effect of population stratification on PI might be inappropriate because it cannot account for the particularities of single paternity cases.