Can the genome size affect the outcome of GWAS?
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The size of the genome can indeed impact the outcome of Genome-Wide Association Studies (GWAS). Different factors such as the number of genotyped individuals, effective population size, and the dimensionality of genomic information play crucial roles in determining the success of GWAS. Studies have shown that the optimal number of genotyped individuals, based on the largest eigenvalues explaining variance in the genomic relationship matrix, can influence the accurate identification of causative variants. Additionally, the efficiency of GWAS in larger samples may vary for different loci, emphasizing the importance of heterogeneity in genetic associations with complex traits. Furthermore, the performance of popular GWAS models can be affected under scenarios of genetic admixture, highlighting the need for caution when interpreting results in complex population scenarios.
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| Yes, gene size, indicated by the number of SNPs, can bias GWAS outcomes. Correction methods are needed for downstream gene-level analysis to address this bias effectively. | |
| Not addressed in the paper. | |
| Yes, the dimensionality of genomic information, influenced by genome size, impacts the effectiveness of GWAS by affecting variant selection and sample size for accurate identification of causative variants. | |
18 Citations | Not addressed in the paper. |
| Not addressed in the paper. |
Related Questions
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