Evaluating methods to correct for population stratification when estimating paternity indexes
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Abstract
The statistical interpretation of the forensic genetic evidence requires the use of allelic frequency estimates in the reference population for the studied markers. Differences in the genetic make up of the populations can be reflected in statistically different allelic frequency distributions. One can easily figure out that collecting such information for any given population is not always possible. Therefore, alternative approaches are needed in these cases in order to compensate for the lack of information. A number of statistics have been proposed to control for population stratification in paternity testing and forensic casework, Fst correction being the only one recommended by the forensic community. In this study we aimed to evaluate the performance of Fst to correct for population stratification in forensics. By way of simulations, we first tested the dependence of Fst on the relative sizes of the sub-populations, and second, we measured the effect of the Fst corrections on the Paternity Index (PI) values compared to the ones obtained when using the local reference database. The results provide clear-cut evidence that (i) Fst values are strongly dependent on the sampling scheme, and therefore, for most situations it would be almost impossible to estimate real values of Fst; and (ii) Fst corrections might unfairly correct PI values for stratification, suggesting the use of local databases whenever possible to estimate the frequencies of genetic profiles and PI values.
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Toscanini U, Garcia-Magariños M, Berardi G, Egeland T, Raimondi E, Salas A (2012) Evaluating Methods to Correct for Population Stratification when Estimating Paternity Indexes. PLoS ONE 7(11): e49832. https://doi.org/10.1371/journal.pone.0049832
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https://doi.org/10.1371/journal.pone.0049832Sponsors
This work was funded by a grant from Ministerio de Ciencia e Innovación (SAF2011-26983) given to AS
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© 2012 Toscanini et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited








