2012
DOI: 10.3378/027.084.0302
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General Method to Unravel Ancient Population Structures through Surnames, Final Validation on Italian Data

Abstract: We analyze the geographic location of 77,451 different Italian surnames (17,579,891 individuals) obtained from the lists of telephone subscribers of the year 1993.By using a specific neural network analysis (Self-Organizing Maps, SOMs), we automatically identify the geographic origin of 49,117 different surnames. To validate the methodology, we compare the results to a study, previously conducted, on the same database, with accurate supervised methods. By comparing the results, we find an overlap of 97%, meani… Show more

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Cited by 24 publications
(20 citation statements)
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“…To best reconstruct the paternal genetic variability of the Partecipanza, we sampled at least one individual for each of the 38 Partecipanza surnames. As for the SGP sample, all the selected individuals share surnames that were identified as autochthonous for the considered area by Boattini et al (2012). To avoid any surname-related bias, all SGP individuals bear different surnames (with the negligible exception of three surnames that are represented by two individuals each).…”
Section: Dna Samplesmentioning
confidence: 99%
See 1 more Smart Citation
“…To best reconstruct the paternal genetic variability of the Partecipanza, we sampled at least one individual for each of the 38 Partecipanza surnames. As for the SGP sample, all the selected individuals share surnames that were identified as autochthonous for the considered area by Boattini et al (2012). To avoid any surname-related bias, all SGP individuals bear different surnames (with the negligible exception of three surnames that are represented by two individuals each).…”
Section: Dna Samplesmentioning
confidence: 99%
“…As a second point, surnames and/or pedigrees can be used for selecting samples within populations. Sampling males bearing surnames that are unequivocally associated with a certain place for Y-chromosome studies provides proxies for older populations (King and Jobling, 2009a;Boattini et al, 2012). The same considerations hold for sample selection based on genealogies/pedigrees.…”
Section: Introductionmentioning
confidence: 99%
“…surnames on the basis of previous works by Zei et al 16,17 Each subject included in the study had a well-defined geographical origin: four grandparents (and parents) born in the same administrative region, assessed through interviews at the time of blood collection. The distribution of the study samples across Italy and the sampling provinces is shown in Figure 1 and Supplementary Table S1 with sample sizes.…”
Section: Introductionmentioning
confidence: 99%
“…For this purpose, 780 individuals were selected to be representative of variation observable at 20 provinces equally distributed in four geographical macro-areas (i.e. Northern Italy, N_ITA; Central Italy, C_ITA; Southern Italy, S_ITA, and Sardinia, SARD) for which previous studies suggested relatively high internal historical/cultural homogeneity325. In addition to ~280,000 genome-wide SNPs, our survey included also ~250,000 exomic markers and ~20,000 variants at coding/regulatory chromosomal intervals with well-established clinical relevance.…”
mentioning
confidence: 99%