Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Low heritabiltiy and genetic correlations #20

Open
demodw opened this issue Mar 23, 2021 · 0 comments
Open

Low heritabiltiy and genetic correlations #20

demodw opened this issue Mar 23, 2021 · 0 comments

Comments

@demodw
Copy link

demodw commented Mar 23, 2021

Hi,

I tried to use HDL to get a more accurate estimate of rg for two phenotype with low heritability. in LDSC the heritabilities are estimated to be 0.0077 (0.0017) and 0.0054 (0.0018). The genetic correlation is -0.18. However, when I run HDL, the heritabilities are estimated to be 0.0044 (0.0013) and 0 (0.002). It's two binary phenotypes, and the sample size is in both cases >248k (N cases + N controls). For both phenotypes, >99% of the SNPs are in the reference. It's a Western European population. I've added a screenshot of the HDL and LDSC output.

What I'm curious about is why the heritability for phenotype 2 is 0, thus making it not possible to estimate rg. Is the heritability of phenotype 2 simply too low, despite being only ~30% lower than phentoype 1, with the ~same standard error? Is there something else I can do to calculate the rg using HDL?

Edit: Looking into the code of HDL, I see that the beta values are approximated using Z / sqrt(N). However, my summary stats includes relateds and was estimated using mixed models. Thus, the N is not entirely correct, I guess. When I compare the bhat.raw versus the observed ones, the bhat.raw is ~10x lower than the estimated one. Could this be an issue?

Thanks in advance.

image

image

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant