title: Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach.
abstract: This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447-2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8-30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics.
authors.affiliation: National Institute on Deafness and Other Communication Disorders, NIH, Bethesda, MD 20854, United States of America; Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of BiGeA, University of Bologna, via Selmi 3, 40126 Bologna, Italy.
authors.forename: Davide
authors.initials: D
authors.lastname: Risso
authors.affiliation: Dipartimento di Biologia, University of Pisa, Via Ghini 13, 56126 Pisa, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Taglioli
authors.affiliation: Dipartimento di Genetica Biologia dei Microrganismi Antropologia Evoluzione, University of Parma, Parco Area delle Scienze 11/a, 43124 Parma, Italy.
authors.forename: Sergio
authors.initials: S
authors.lastname: De Iasio
authors.affiliation: Dipartimento di Scienze Statistiche, University of Bologna, Via Belle Arti 41, 40126 Bologna, Italy.
authors.forename: Paola
authors.initials: P
authors.lastname: Gueresi
authors.affiliation: Bocconi University, Dondena Centre and IGIER, Milan, Italy.
authors.forename: Guido
authors.initials: G
authors.lastname: Alfani
authors.affiliation: Archivio di Stato, Lucca, Italy.
authors.forename: Sergio
authors.initials: S
authors.lastname: Nelli
authors.affiliation: Dipartimento di Fisica, University of Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy.
authors.forename: Paolo
authors.initials: P
authors.lastname: Rossi
authors.affiliation: Dipartimento di Biologia, University of Pisa, Via Ghini 13, 56126 Pisa, Italy.
authors.forename: Giorgio
authors.initials: G
authors.lastname: Paoli
authors.affiliation: Dipartimento di Biologia, University of Pisa, Via Ghini 13, 56126 Pisa, Italy.
authors.forename: Sergio
authors.initials: S
authors.lastname: Tofanelli
mesh_terms: D003710:Demography / Q000706:statistics & numerical data; D040961:Genetic Drift; D005828:Genetics, Population / Q000706:statistics & numerical data*; D005843:Geography; D006801:Humans; D008297:Male; D009275:Names; D011336:Probability; D012111:Residence Characteristics / Q000706:statistics & numerical data; D015983:Selection Bias