Cambridge University Press
SM1. Raw results from DIYABC software of the 25 first scenarios, presenting a PCA, allowing us to visualize how data sets simulated under each scenario are close or not from the observed data set (yellow dot). The most relevant scenarios chosen were the first 6.-50482531940500SM 2. Pairwise probability values for linkage disequilibrium among 19 microsatellite loci. None of the test resulted significant (experiment wise a=0.05) after False Discovery Rate correction (Benjamini and Hochberg 1995b).ppppH9-F340.007F4-F160.203C3-E430.462E43-F320.769D3-B520.009D3-E340.214G1-C330.465B52-F140.777G1-B520.012E34-E430.223H10-F340.487H9-F160.780E43-G340.015C3-G340.228C3-F320.492G1-H70.781C3-F30.022H10-E430.228C3-H100.496F3-F320.783D11-H90.022F14-F340.228E8-F140.503G1-H100.798G1-G340.022E8-G340.239G1-E430.507E34-F320.816D3-E80.024D11-F160.242F3-E340.511C3-F140.822H10-F160.025D3-G10.243D11-F140.512D3-D110.836E8-H100.026E34-F160.252D3-H70.513E8-H90.841E8-C330.035H10-F320.253H7-C330.536F16-G340.843D3-F320.036F14-G340.264B52-F160.551H9-G340.856F3-E430.038H7-H90.273E8-F30.555C3-B520.860D11-F30.040D11-H100.286F3-G10.561B52-E430.866C3-D30.041B52-F320.288H10-G340.564C33-E430.866F4-E340.041E43-F140.288H9-E340.585F16-F320.870D3-F30.044F34-G340.295F3-H70.593H7-E430.873E34-G340.044C3-D110.311C3-F340.595H9-H100.875D3-C330.045F4-H90.311C33-F160.595F3-F140.886B52-G340.051H7-G340.312E34-F340.599H10-C330.890D3-H90.054F32-F340.312C3-G10.605H9-B520.892D11-B520.058E8-F340.316E8-E430.621E8-F40.896D3-F40.065F3-H100.332H9-F140.622D11-F340.907E8-G10.081D3-F340.339F4-H100.630F4-F340.907D3-H100.083D3-F160.341C3-F40.636G1-E340.907H9-C330.101D3-E430.346F3-F40.652C3-F160.914D3-F140.113F4-C330.349D11-E80.675B52-C330.916F14-F160.113F4-E430.358C33-F320.677H7-F340.920H10-E340.144H10-B520.381F16-F340.677F14-F320.926D11-G10.145G1-H90.384F4-G10.678D11-E340.928D11-H70.148E34-F140.389F4-F140.681F3-H90.929D11-G340.148G1-F160.396H7-F140.682D11-F40.946F4-H70.149E8-F320.399F4-G340.685F3-C330.946F3-F160.153H7-F160.400C3-H70.694E8-F160.970B52-F340.157H10-F140.402E8-B520.697H9-F320.984C33-E340.182F3-B520.405F4-F320.707C3-C330.988E43-F160.185G1-F320.406E8-H70.712H7-H100.989H9-E430.188C3-E80.409E43-F340.718E8-E340.990G1-F340.189C3-H90.416C3-E340.721D11-E430.991H7-B520.191B52-E340.422D11-C330.744D11-F321.000F3-F340.195G1-F140.441C33-G340.753H7-F321.000F4-B520.195C33-F340.445H7-E340.759F32-G341.000C33-F140.201D3-G340.458F3-G340.76330480132969000SM3. Posterior predictive maps of admixture proportions as obtained from the interpolation of co-ancestry coefficients resulting from STRUCTURE (Fig. 2) and the geographic distribution of 332 African specimens of Z. cucurbitae (Table 1). SM 4. Average assignment of log likelihood (–LogL) of individuals from each African populations of fruit flies sampled (n=12) and a putative source population (Asia) as calculated by GENECLASS2 Piry et al. 2004. LINK Excel.Sheet.12 "D:\\Mes Données\\soumis\\soumis 2018\\ms cucurbitae\\soumission review 2018\\log10.xlsx" Feuil3!L27C3:L42C18 \a \f 4 \h \* MERGEFORMAT ?AsiaSenegalGuineaIvory CoastBurkina FasoTogoBeninCongoSudanBurundiUgandaKenyaTanzaniaaverageSEAsia0.720.050.020.030.110.040.020.010.020.010.010.060.000.030.01Senegal0.400.660.460.590.620.610.580.090.520.230.200.400.180.410.05Guinea0.460.620.620.610.640.620.590.110.560.260.310.470.230.460.05Ivory Coast0.400.580.390.720.650.540.560.070.390.180.140.400.130.370.06Burkina Faso0.590.610.390.630.770.560.540.100.460.220.300.440.190.420.05Togo0.470.640.440.590.640.670.560.100.370.160.220.370.130.390.06Benin0.430.620.440.620.660.560.700.030.410.130.220.380.050.380.06Congo0.760.690.590.740.760.700.580.730.540.240.350.530.220.560.06Sudan0.520.690.540.620.680.570.550.090.610.280.340.570.210.470.06Burundi0.490.700.520.630.660.650.590.050.550.710.220.620.440.510.06Uganda0.610.550.450.580.670.560.580.070.460.230.600.590.130.460.06Kenya0.480.470.390.540.580.490.470.090.410.190.290.710.110.370.05Tanzania0.550.620.370.530.640.510.430.080.420.410.210.540.670.440.05average0.510.570.420.560.610.530.500.070.420.210.230.450.17??SE0.030.050.040.050.050.050.050.010.040.030.030.040.03??SM5. Raw results from DIYABC software of the best 6 scenarios, presenting the (above graph) posterior probabilities of scenarios obtained through a logistic regression, computed every 10% (between 10 and 100%) of the number of selected data sets. The below graph is presenting a PCA, allowing us to visualize how data sets simulated under each scenario are close or not from the observed data set (yellow dot). The most relevant scenario chosen was scenario 6.111633023241000-599440270446500-723265424497500 ................
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