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