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1. Additional file 11 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Abstract

Additional file 11: Figure S8. Log scale QQ-plots corresponding to association analysis performed independently on each trait and repetition. Three different models (i.e. EMMA, LFMM, MLM) taking into account relatedness and/or structure were used for association and ANOVA was used as a benchmark. For a given trait, the transformed data were used if at least one of the replicates failed to reach normality, otherwise non-transformed data were used.

Published
2020
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2. Additional file 8 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Abstract

Additional file 8: Figure S5. Correlations between traits and structure. For each ancestry group (A1 to A4), we made a Spearman’s rank correlation test and plotted it as a correlogram. Colors sign the intensity of the correlation and white stars were added when the correlation was significant given the threshold retained, i.e. either a p-value cutoff of 0.01 (a) or a False Discovery Rate of 5% (b).

Published
2020
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3. Additional file 5 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Abstract

Additional file 5: Figure S2. Genome wide Linkage disequilibrium (LD) decay.

Published
2020
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4. Additional file 10 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Abstract

Additional file 10: Figure S7. Manhattan plots. Association analysis were performed independently for each trait and repetition and based on three different methods (EMMA, LFMM, MLM). The transformed data were used if at least one of the replicates failed to reach normality. P-values obtained for each replicate were then combined using a Fisher combined probability test method to obtain the final p-values represented in this Manhattan plots. The 10− 5 thresholds are indicated by red lines.

Published
2020
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5. Additional file 9 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Abstract

Additional file 9: Figure S6. Linear scale QQ-plots corresponding to association analysis performed independently on each trait and repetition. Three different methods (EMMA, LFMM, MLM) taking into account relatedness and/or structure were used for association and ANOVA was used as a benchmark. For a given trait, the transformed data were used if at least one of the replicates failed to reach normality, otherwise non-transformed data were used.

Published
2020
Full Text
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6. Additional file 6 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Subjects
2. Zero hunger
Abstract

Additional file 6: Figure S3. Structure of the population. (a) evolution of the cross-entropy criterion with increasing K, (b) bar plot of ancestries membership considering K = 4 ancestral population.

7. Additional file 7 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Subjects
2. Zero hunger
Abstract

Additional file 7: Figure S4. Geographic distribution of traits. We plotted the mean value of each trait for accessions having sampling location in their passport data.

8. Additional file 3 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Subjects
2. Zero hunger
Abstract

Additional file 3: Figure S1. Histograms of trait distribution and quantile-quantile plots for each non-transformed and transformed variables.

9. Additional file 3 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Subjects
2. Zero hunger
Abstract

Additional file 3: Figure S1. Histograms of trait distribution and quantile-quantile plots for each non-transformed and transformed variables.

10. Additional file 7 of Genome Wide Association Study Pinpoints Key Agronomic QTLs in African Rice Oryza glaberrima

Author

Cubry, Philippe, Pidon, Hélène, Ta, Kim Nhung, Tranchant-Dubreuil, Christine, Anne-Céline Thuillet, Holzinger, Maria, Adam, Hélène, Kam, Honoré, Chrestin, Harold, Ghesquière, Alain, François, Olivier, Sabot, François, Vigouroux, Yves, Albar, Laurence, and Jouannic, Stefan

Subjects
2. Zero hunger
Abstract

Additional file 7: Figure S4. Geographic distribution of traits. We plotted the mean value of each trait for accessions having sampling location in their passport data.

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