DOI: 10.6084/m9.figshare.26299302
title: Additional file 1 of Evaluation of heritability partitioning approaches in livestock populations

description: Additional file 1. Supplementary Tables. Table S1. %SNP heritability estimation when variants in open chromatin regions account for 50% of the heritability. Table S2. %SNP heritability estimation when causal variants are enriched in low MAF variants. Table S3. %SNP heritability estimation when causal variants are enriched in low LD score variants. Table S4. %SNP heritability estimation when causal variants are enriched in low MAF and LD score variants. Table S5. %SNP heritability estimation when causal variants are enriched in common variants. Table S6. %SNP heritability estimation when causal variants are enriched in high LD score variants. Table S7. %SNP heritability estimation when causal variants are enriched in low MAF and high LD score variants. Table S8. %SNP heritability estimation with multiple functional categories when the variants in coding sequence account for 100% of the heritability. Table S9. %SNP heritability estimation with multiple functional categories when the variants in intronic regions account for 100% of the heritability. Table S10. %SNP heritability estimation with multiple functional categories when the variants in upstream and downstream regions account for 100% of the heritability. Table S11. %SNP heritability estimation with multiple functional categories when the variants in intergenic regions account for 100% of the heritability. Table S12. %SNP heritability estimation with multiple functional categories when the variants in open chromatin regions account for 100% of the heritability. Table S13. %SNP heritability estimation with multiple functional categories when the variants from different functional classes had equal contribution. Table S14. %SNP heritability estimation in complex simulation scenarios where SNPs from different functional classes had variable contributions (scenario I). Table S15. %SNP heritability estimation in complex simulation scenarios where SNPs from different functional classes had variable contributions (scenario II). Table S16. %SNP heritability estimation in complex simulation scenarios where SNPs from different functional classes had variable contributions (scenario III). Table S17. Mean Absolute Error of %SNP heritability estimates across the three complex simulation scenarios where SNPs from different functional classes had variable contributions. Table S18. %SNP heritability estimation with a two-component approach when the variants from different functional classes had equal contribution. Table S19. %SNP heritability estimation with a two-component approach in complex simulation scenarios where SNPs from different functional classes had variable contributions (scenario I). Table S20. %SNP heritability estimation with a two-component approach in complex simulation scenarios where SNPs from different functional classes had variable contributions (scenario II). Table S21. %SNP heritability estimation with a two-component approach in complex simulation scenarios where SNPs from different functional classes had variable contributions (scenario III). Table S22. Mean Absolute Error of %SNP heritability estimates using a two-component approach across the three complex simulation scenarios where SNPs from different functional classes had variable contributions. Table S23. Correlations between genomic relationship matrices from different functional categories. Table S24. %SNP heritability estimation for the measured phenotypes. Table S25. Heritability enrichment estimation for the measured phenotypes. Table S26. %SNP heritability and heritability enrichment estimation using a LDMS two component approach for the measured phenotypes.