Error: the variance-covaraince matrix V is not invertible in GCTA / genetic correlation
Entering edit mode
3.9 years ago
anamaria ▴ 220


I am not sure if this is a good thing to do but I was trying to assess genetic correlation using bivariate GREML as implemented in the GCTA on a single set of subjects. In detail I have some old imputed data and I do have a new imputed data on the same subjects so I was running bivariate analysis where in pheno file I have one trait case/control designation for old data and another traint case/control designation for new data. My pheno file looks like this:

> head(a)
  FID          IID new old
1   0 fam0110_G110   2   2
2   0 fam0113_G113   2   2
3   0 fam0114_G114   2   2
4   0 fam0117_G117   2   2
5   0 fam0119_G119   1   1
7   0 fam0127_G127   2   2

And I was running this:

./gcta64 --reml-bivar --grm Merge  --pheno combined_old_new   --out GCTA_trait2

I got:

Error: the variance-covaraince matrix V is not invertible.

Is it not possible to run this analysis if the cases and controls are the same?

What else I can do to calculate genetic correlation? I don't have GWAS summary stats (if I do I would do LDSC) I only have genotype data.

Please advise,

gcta genetic correlation • 1.6k views

Login before adding your answer.

Traffic: 2691 users visited in the last hour
Help About
Access RSS

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6