D. Achlioptas and F. Mcsherry, Fast computation of low-rank matrix approximations, Journal of the ACM, vol.54, issue.2, p.9, 2007.
DOI : 10.1145/1219092.1219097

D. Altshuler, E. Lander, L. Ambrogio, T. Bloom, K. Cibulskis et al., and others . A map of human genome variation from population scale sequencing, Nature, issue.7319, pp.4671061-1073, 2010.

G. Barbujani and R. Sokal, Zones of sharp genetic change in Europe are also linguistic boundaries., Proceedings of the National Academy of Sciences, pp.1816-1819, 1990.
DOI : 10.1073/pnas.87.5.1816

G. Barbujani and N. Oden, Detecting Regions of Abrupt Change in Maps of Biological Variables, Systematic Zoology, vol.38, issue.4, pp.376-389, 1989.
DOI : 10.2307/2992403

M. Beaumont and B. Rannala, The Bayesian revolution in genetics, Nature Reviews Genetics, vol.49, issue.4, pp.251-261, 2004.
DOI : 10.1093/molbev/msg043

M. A. Beaumont, Approximate Bayesian Computation in Evolution and Ecology, Annual Review of Ecology, Evolution, and Systematics, vol.41, issue.1, pp.379-406, 2010.
DOI : 10.1146/annurev-ecolsys-102209-144621

M. A. Beaumont, W. Zhang, and D. J. Balding, Approximate Bayesian computation in population genetics, Genetics, vol.162, pp.2025-2035, 2002.

M. A. Beaumont, J. Cornuet, J. Marin, and R. C. , Adaptive approximate Bayesian computation, Biometrika, vol.96, issue.4, pp.983-990, 2009.
DOI : 10.1093/biomet/asp052

URL : https://hal.archives-ouvertes.fr/hal-00280461

G. Biau, F. Cérou, and A. Guyader, New insights into Approximate Bayesian Computation, Annales de l'Institut Henri Poincar??, Probabilit??s et Statistiques, vol.51, issue.1, 2012.
DOI : 10.1214/13-AIHP590

URL : https://hal.archives-ouvertes.fr/hal-00721164

C. Bishop, Pattern recognition and machine learning, 2006.

S. Blomberg, G. Jr, T. Ives, and A. , TESTING FOR PHYLOGENETIC SIGNAL IN COMPARATIVE DATA: BEHAVIORAL TRAITS ARE MORE LABILE, Evolution, vol.31, issue.4, pp.717-745, 2003.
DOI : 10.1016/S0006-3207(97)00179-1

M. G. Blum, Approximate Bayesian Computation: A Nonparametric Perspective, Journal of the American Statistical Association, vol.105, issue.491, pp.1178-1187, 2010.
DOI : 10.1198/jasa.2010.tm09448

URL : https://hal.archives-ouvertes.fr/hal-00373301

M. G. Blum and O. François, Non-linear regression models for Approximate Bayesian Computation, Statistics and Computing, vol.72, issue.1, pp.63-73, 2010.
DOI : 10.1007/s11222-009-9116-0

URL : http://arxiv.org/abs/0809.4178

M. G. Blum and M. Jakobsson, Deep Divergences of Human Gene Trees and Models of Human Origins, Molecular Biology and Evolution, vol.28, issue.2, pp.889-898, 2011.
DOI : 10.1093/molbev/msq265

URL : https://hal.archives-ouvertes.fr/hal-00775893

M. G. Blum, M. Nunes, D. Prangle, and S. Sisson, A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation, Statistical Science, vol.28, issue.2, 2012.
DOI : 10.1214/12-STS406SUPP

URL : https://hal.archives-ouvertes.fr/hal-00861839

J. Bocquet-appel, J. Bacro, and . Wombling, Generalized Wombling, Systematic Biology, vol.43, issue.3, pp.442-448, 1994.
DOI : 10.1093/sysbio/43.3.442

URL : http://sysbio.oxfordjournals.org/cgi/content/short/43/3/442

P. Carbonetto and M. Stephens, Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies, Bayesian Analysis, vol.7, issue.1, pp.73-108, 2012.
DOI : 10.1214/12-BA703

C. M. Carvalho, J. Chang, J. E. Lucas, J. R. Nevins, Q. Wang et al., High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics, Journal of the American Statistical Association, vol.103, issue.484, pp.1438-1456, 2008.
DOI : 10.1198/016214508000000869

L. Cavalli-sforza and G. Zei, Experiments with an artificial population, Proceedings of the Third International Congress of Human Genetics, pp.473-478, 1967.

L. Cavalli-sforza, P. Menozzi, and A. Piazza, The history and geography of human genes, 1994.

A. Cercueil and O. François, The Genetical Bandwidth Mapping: A spatial and graphical representation of population genetic structure based on the Wombling method, Theoretical Population Biology, vol.71, issue.3, pp.332-341, 2007.
DOI : 10.1016/j.tpb.2007.01.007

URL : https://hal.archives-ouvertes.fr/halsde-00283758

J. Cornuet, V. Ravigné, and A. Estoup, Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0), BMC Bioinformatics, vol.11, issue.1, p.401, 2010.
DOI : 10.1186/1471-2105-11-401

N. Cressie, Statistics for spatial data, 1992.
DOI : 10.1002/9781119115151

K. Csilléry, M. G. Blum, O. Gaggiotti, and O. François, Approximate Bayesian Computation (ABC) in practice, Trends in Ecology & Evolution, vol.25, issue.7, pp.410-418, 2010.
DOI : 10.1016/j.tree.2010.04.001

K. Csilléry, O. François, and M. G. Blum, abc : an R package for approximate Bayesian computation (ABC). Methods in ecology and evolution, pp.475-479, 2012.

D. Moral, P. Doucet, A. Jasra, and A. , An adaptive sequential Monte Carlo method for approximate Bayesian computation, Statistics and Computing, vol.6, issue.5, pp.1009-1020, 2012.
DOI : 10.1007/s11222-011-9271-y

P. J. Diggle and R. J. Gratton, Monte Carlo methods of inference for implicit statistical models, Journal of the Royal Statistical Society. Series B (Methodological), pp.193-227, 1984.

K. Doksum and A. Lo, Consistent and robust Bayes procedures for location based on partial information. The Annals of Statistics, pp.443-453, 1990.
DOI : 10.1214/aos/1176347510

URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1176347510

A. Drummond and A. Rambaut, BEAST: Bayesian evolutionary analysis by sampling trees, BMC Evolutionary Biology, vol.7, issue.1, p.214, 2007.
DOI : 10.1186/1471-2148-7-214

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2247476

N. Duforet-frebourg and M. G. Blum, Non-stationary patterns of isolation-by-distance : inferring measures of genetic friction, 2012.

B. Engelhardt and M. Stephens, Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis, PLoS Genetics, vol.81, issue.9, p.1001117, 2010.
DOI : 10.1371/journal.pgen.1001117.s003

P. Fearnhead and D. Prangle, Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.31, issue.3, pp.419-474, 2012.
DOI : 10.1111/j.1467-9868.2011.01010.x

O. François, M. Currat, N. Ray, E. Han, L. Excoffier et al., Principal Component Analysis under Population Genetic Models of Range Expansion and Admixture, Molecular Biology and Evolution, vol.27, issue.6, pp.1257-1268, 2010.
DOI : 10.1093/molbev/msq010

E. Frichot, S. Schoville, G. Bouchard, and O. François, Landscape genomic tests for associations between loci and environmental gradients, 2012.
DOI : 10.1093/molbev/mst063

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3684853

R. Green, J. Krause, A. Briggs, T. Maricic, U. Stenzel et al., and others . A draft sequence of the Neandertal genome, Science, issue.5979, pp.328710-722, 2010.

F. Gugerli, T. Englisch, H. Niklfeld, A. Tribsch, Z. Mirek et al., Relationships among levels of biodiversity and the relevance of intraspecific diversity in conservation ??? a project synopsis, Perspectives in Plant Ecology, Evolution and Systematics, vol.10, issue.4, pp.259-281, 2008.
DOI : 10.1016/j.ppees.2008.07.001

URL : https://hal.archives-ouvertes.fr/halsde-00377966

G. Guillot and F. Rousset, On the use of the simple and partial Mantel tests in presence of spatial autocorrelation, 2011.

J. Hadfield, MCMC methods for multi-response generalized linear mixed models : the MCMCglmm R package, Journal of Statistical Software, vol.33, issue.2, pp.1-22, 2010.

M. Handcock and M. Stein, A Bayesian Analysis of Kriging, Technometrics, vol.21, issue.3, pp.403-410, 1993.
DOI : 10.1080/00401706.1993.10485354

B. E. Hansen, Nonparametric conditional density estimation, 2004.

O. Hardy and X. Vekemans, Isolation by distance in a continuous population: reconciliation between spatial autocorrelation analysis and population genetics models, Heredity, vol.31, issue.2, pp.145-154, 1999.
DOI : 10.1046/j.1365-2540.1999.00518.x

S. Hoban, G. Bertorelle, and O. Gaggiotti, Computer simulations: tools for population and evolutionary genetics, Nature Reviews Genetics, vol.11, 2012.
DOI : 10.1038/nrg3130

URL : http://hdl.handle.net/10261/61212

A. Hoerl and R. Kennard, Ridge Regression: Biased Estimation for Nonorthogonal Problems, Technometrics, vol.24, issue.1, pp.55-67, 1970.
DOI : 10.2307/1909769

K. Holsinger and B. Weir, Genetics in geographically structured populations: defining, estimating and interpreting FST, Nature Reviews Genetics, vol.97, issue.9, pp.639-650, 2009.
DOI : 10.1038/nrg2611

R. R. Hudson, Generating samples under a Wright-Fisher neutral model of genetic variation, Bioinformatics, vol.18, issue.2, pp.337-338, 2002.
DOI : 10.1093/bioinformatics/18.2.337

R. J. Hyndman, D. M. Bashtannyk, and G. G. , Estimating and visualizing conditional densities, Journal of Computing and Graphical Statistics, vol.5, pp.315-336, 1996.
DOI : 10.1080/10618600.1996.10474715

G. Jacquez, S. Maruca, and M. Fortin, From fields to objects: A review of geographic boundary analysis, Journal of Geographical Systems, vol.2, issue.3, pp.221-241, 2000.
DOI : 10.1007/PL00011456

M. Jakobsson, S. Scholz, P. Scheet, J. Gibbs, J. Vanliere et al., Genotype, haplotype and copy-number variation in worldwide human populations, Nature, vol.115, issue.7181, pp.451998-1003, 2008.
DOI : 10.1038/nature06742

F. Jay, O. François, and M. G. Blum, Predictions of Native American Population Structure Using Linguistic Covariates in a Hidden Regression Framework, PLoS ONE, vol.10, issue.1, p.16227, 2011.
DOI : 10.1371/journal.pone.0016227.s006

URL : https://hal.archives-ouvertes.fr/hal-00655073

F. Jay, S. Manel, N. Alvarez, E. Y. Durand, W. Thuiller et al., Forecasting changes in population genetic structure of alpine plants in response to global warming, Molecular Ecology, vol.459, issue.10, 2012.
DOI : 10.1111/j.1365-294X.2012.05541.x

URL : https://hal.archives-ouvertes.fr/hal-00775883

F. Jay, P. Sjodïn, M. Jakobsson, and M. G. Blum, Anisotropic Isolation by Distance: The Main Orientations of Human Genetic Differentiation, Molecular Biology and Evolution, vol.30, issue.3, 2013.
DOI : 10.1093/molbev/mss259

URL : https://hal.archives-ouvertes.fr/hal-00775881

I. Jolliffe, Principal component analysis, 2005.
DOI : 10.1007/978-1-4757-1904-8

P. Joyce and P. Marjoram, Approximately Sufficient Statistics and Bayesian Computation, Statistical Applications in Genetics and Molecular Biology, vol.7, issue.1, 2008.
DOI : 10.2202/1544-6115.1389

M. Kimura and G. Weiss, The stepping stone model of population structure and the decrease of genetic correlation with distance, Genetics, vol.49, issue.4, p.561, 1964.

N. Le and J. Zidek, Interpolation with uncertain spatial covariances: A Bayesian alternative to Kriging, Journal of Multivariate Analysis, vol.43, issue.2, pp.351-374, 1992.
DOI : 10.1016/0047-259X(92)90040-M

P. Legendre, Comparison of permutation methods for the partial correlation and partial mantel tests, Journal of Statistical Computation and Simulation, vol.50, issue.1, pp.37-73, 2000.
DOI : 10.2307/1392523

S. Manel, M. Schwartz, G. Luikart, and P. Taberlet, Landscape genetics: combining landscape ecology and population genetics, Trends in Ecology & Evolution, vol.18, issue.4, pp.189-197, 2003.
DOI : 10.1016/S0169-5347(03)00008-9

URL : https://hal.archives-ouvertes.fr/halsde-00279786

F. Manni, E. Guerard, and E. Heyer, Geographic Patterns of (Genetic, Morphologic, Linguistic) Variation: How Barriers Can Be Detected by Using Monmonier's Algorithm, Human Biology, vol.76, issue.2, pp.173-190, 2004.
DOI : 10.1353/hub.2004.0034

J. Marin, P. Pudlo, C. P. Robert, and R. J. Ryder, Approximate Bayesian computational methods, Statistics and Computing, vol.6, issue.31, pp.1-14, 2011.
DOI : 10.1007/s11222-011-9288-2

URL : https://hal.archives-ouvertes.fr/hal-00567240

P. Marko and M. Hart, The complex analytical landscape of gene flow inference. Trends in ecology & evolution, pp.448-456, 2011.

C. Mcculloch and J. Neuhaus, Generalized linear mixed models, 2005.

B. Mcrae and P. Beier, Circuit theory predicts gene flow in plant and animal populations, Proceedings of the National Academy of Sciences, pp.19885-19890, 2007.
DOI : 10.1073/pnas.0706568104

G. Mcvean, A Genealogical Interpretation of Principal Components Analysis, PLoS Genetics, vol.27, issue.10, p.1000686, 2009.
DOI : 10.1371/journal.pgen.1000686.g006

M. Monmonier, Maximum-Difference Barriers: An Alternative Numerical Regionalization Method*, Geographical Analysis, vol.58, issue.3, pp.245-261, 1973.
DOI : 10.1111/j.1538-4632.1973.tb01011.x

J. Novembre and M. Stephens, Interpreting principal component analyses of spatial population genetic variation, Nature Genetics, vol.447, issue.5, pp.646-649, 2008.
DOI : 10.1093/biostatistics/kxl008

M. A. Nunes and D. J. Balding, On Optimal Selection of Summary Statistics for Approximate Bayesian Computation, Statistical Applications in Genetics and Molecular Biology, vol.9, issue.1, 2010.
DOI : 10.2202/1544-6115.1576

C. Paciorek and M. Schervish, Spatial modelling using a new class of nonstationary covariance functions, Environmetrics, vol.99, issue.5, pp.483-506, 2006.
DOI : 10.1002/env.785

M. Pagel, Detecting Correlated Evolution on Phylogenies: A General Method for the Comparative Analysis of Discrete Characters, Proceedings of the Royal Society of London. Series B : Biological Sciences, pp.25537-25582, 1342.
DOI : 10.1098/rspb.1994.0006

N. Patterson, A. Price, and D. Reich, Population Structure and Eigenanalysis, PLoS Genetics, vol.15, issue.12, p.190, 2006.
DOI : 1088-9051(2005)015[1576:CACSOH]2.0.CO;2

URL : http://doi.org/10.1371/journal.pgen.0020190

J. Pritchard, M. Stephens, and P. Donnelly, Inference of population structure using multilocus genotype data, Genetics, vol.155, issue.2, pp.945-959, 2000.

J. K. Pritchard, M. T. Seielstad, A. Perez-lezaun, and M. W. Feldman, Population growth of human Y chromosomes: a study of Y chromosome microsatellites, Molecular Biology and Evolution, vol.16, issue.12, pp.1791-1798, 1999.
DOI : 10.1093/oxfordjournals.molbev.a026091

N. Raufaste and F. Rousset, Are partial Mantel tests adequate ? Evolution, pp.1703-1705, 2001.
DOI : 10.1554/0014-3820(2001)055[1703:apmta]2.0.co;2

B. Ripley, Neural networks and related methods for classification, Journal of the Royal Statistical Society. Series B (Methodological), pp.409-456, 1994.

C. P. Robert, J. Cornuet, J. Marin, and P. N. , Lack of confidence in approximate Bayesian computation model choice, Proceedings of the National Academy of Sciences, pp.15112-15117, 2011.
DOI : 10.1073/pnas.1102900108

URL : https://hal.archives-ouvertes.fr/hal-00596300

F. Rousset, Genetic differentiation and estimation of gene flow from F-statistics under isolation by distance, Genetics, vol.145, issue.4, pp.1219-1228, 1997.

D. Rubin, Bayesianly justifiable and relevant frequency calculations for the applies statistician. The Annals of Statistics, pp.1151-1172, 1984.

N. Saitou and M. Nei, The neighbor-joining method : a new method for reconstructing phylogenetic trees, Molecular biology and evolution, vol.4, issue.4, pp.406-425, 1987.

M. Schwartz and K. Mckelvey, Why sampling scheme matters: the effect of sampling scheme on landscape genetic results, Conservation Genetics, vol.62, issue.2, pp.441-452, 2009.
DOI : 10.1007/s10592-008-9622-1

D. W. Scott, Multivariate density estimation, 1992.

M. A. Sedki and P. Pudlo, Contribution to the discussion of Fearnhead and Prangle (2012) Constructing summary statistics for approximate Bayesian computation : Semi-automatic approximate Bayesian computation, Journal of the Royal Statistical Society : Series B, vol.74, pp.466-467, 2012.

V. Segura, B. Vilhjálmsson, A. Platt, A. Korte, Ü. Seren et al., An efficient multilocus mixed-model approach for genome-wide association studies in structured populations, Nature genetics, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01267792

D. Seung and L. Lee, Algorithms for non-negative matrix factorization Advances in neural information processing systems, pp.556-562, 2001.

S. Sisson, Y. Fan, and M. Tanaka, Sequential Monte Carlo without likelihoods, Proceedings of the National Academy of Sciences, pp.1760-1765, 2007.
DOI : 10.1073/pnas.0607208104

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1794282

M. Slatkin, Isolation by Distance in Equilibrium and Non-Equilibrium Populations, Evolution, vol.47, issue.1, pp.264-279, 1993.
DOI : 10.2307/2410134

R. Sokal and N. Oden, Spatial autocorrelation in biology: 1. Methodology, Biological Journal of the Linnean Society, vol.10, issue.2, pp.199-228, 1978.
DOI : 10.1111/j.1095-8312.1978.tb00013.x

R. Sokal, F. Rohlf, and . Biometry, WH Freman and company, 1995.

R. Sokal and D. Wartenberg, A test of spatial autocorrelation analysis using an isolation-by-distance model, Genetics, vol.105, issue.1, pp.219-237, 1983.

A. Storfer, M. Murphy, S. Spear, R. Holderegger, and L. Waits, Landscape genetics: where are we now?, Molecular Ecology, vol.15, issue.17, pp.3496-3514, 2010.
DOI : 10.1111/j.1365-294X.2010.04691.x

S. Tavaré, Ancestral inference in population genetics. Lectures on probability theory and statistics, pp.1931-1931, 2004.

A. Templeton, Coherent and incoherent inference in phylogeography and human evolution, Proceedings of the National Academy of Sciences, p.6376, 2010.
DOI : 10.1073/pnas.0910647107

M. Tipping and C. Bishop, Mixtures of Probabilistic Principal Component Analyzers, Neural Computation, vol.2, issue.1, pp.443-482, 1999.
DOI : 10.1007/BF00162527

W. Tobler, A Computer Movie Simulating Urban Growth in the Detroit Region, Economic Geography, vol.46, pp.234-240, 1970.
DOI : 10.2307/143141

D. Wegmann, C. Leuenberger, and L. Excoffier, Efficient Approximate Bayesian Computation Coupled With Markov Chain Monte Carlo Without Likelihood, Genetics, vol.182, issue.4, pp.1207-1218, 2009.
DOI : 10.1534/genetics.109.102509

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2728860

B. Weir and C. Cockerham, Estimating F-Statistics for the Analysis of Population Structure, Evolution, vol.38, issue.6, pp.1358-1370, 1984.
DOI : 10.2307/2408641

W. Womble, Differential Systematics, Science, vol.114, issue.2961, pp.315-322, 1951.
DOI : 10.1126/science.114.2961.315

S. Wright, Isolation by distance, Genetics, vol.28, issue.2, p.114, 1943.

J. Yu, G. Pressoir, W. Briggs, I. Bi, M. Yamasaki et al., A unified mixed-model method for association mapping that accounts for multiple levels of relatedness, Nature Genetics, vol.2, issue.2, pp.203-208, 2005.
DOI : 10.1038/ng1702