**10**wrote:

Dear all,

I am running a differential expression analysis with limma. My dataset includes unrelated individuals as well as twins, and I am aware that limma is not designed to deal with familiar data, but, as explained in the users' guide I may use the family as a blocking variable (in this way limma will estimate a within-family correlation from the expression data and will use it for the differential analysis).

Unfortunately, when running lmFit with the correlation factor I get this error:

Error in chol.default(V) :

the leading minor of order 2 is not positive definite

I understand that this depends on my data structure, and clearly I do not have a positive definite matrix, therefore it doesn't respect the assumptions of cholesky decomposition. But do you have any suggestion on how to overcome the problem?

This is the code I am using:

formula <- ~ condition

design <- model.matrix(formula, data=info)

corfit <- duplicateCorrelation(eset, design, block=info$famID)

fit <- lmFit(eset, design, block=info$famID, correlation=corfit.corr$consensus)

Thanks in advance

**5.9k**• written 4.4 years ago by iside •

**10**

I have the same problem with lmFit! Have you found any solution yet? I have log2 transformed data as well.

Thanks a lot!

10