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Comment
. 2015 Oct 6;112(40):E5452-3.
doi: 10.1073/pnas.1511370112. Epub 2015 Sep 28.

Reply to Lee: Downward bias in heritability estimation is not due to simplified linkage equilibrium SNP simulation

David Golan  1 , Saharon Rosset  2 , Eric S Lander  3
Affiliations
Comment

Reply to Lee: Downward bias in heritability estimation is not due to simplified linkage equilibrium SNP simulation

David Golan et al. Proc Natl Acad Sci U S A. .
No abstract available

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
The correlation between the top principal component and the phenotype depends on the number of genotyped SNPs and not only on the number of causal SNPs. We used our method (3) to simulate GWAS of 1,280 individuals as in Dr. S. H. Lee’s letter (2), fixing the number of causal SNPs to 100, but changing the overall number of SNPs from 100 to 1,000–10,000. It is apparent that, as expected according to random matrix theory, as the number of genotyped SNPs increases, the correlation between the top PC and the phenotype diminishes. Importantly, because we simulate 10,000 “effective” SNPs, these simulations are equivalent to simulating roughly 100,000 SNPs with realistic linkage disequilibrium. In our paper, we used simulations with 10,000 SNPs, which do not present the unrealistic eigenstructure observed by Dr. S. H. Lee.
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References

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