**70**wrote:

I want to find correlations between change in log2(gene expression) and change in log2(VO2max) from time A1 -> B1, adjusted for group and including the fact that the samples are paired. I get this error:

*"Error in glmFit.default(y, design = design, dispersion = dispersion, offset = offset, :
Design matrix not of full rank. The following coefficients not estimable:
ID79"*

Is this due to some linear dependencies? How get I get the results I want?

VO2max <- as.numeric(pData.myoglu[ 1:52, 6]) # (Random numbers as I can't post the original here)

Time <- factor(pData.myoglu[ 1:52, 4], levels=c("A1", "B1"))

Status <- factor(pData.myoglu[ 1:52, 2], levels=c("control", "IGT"))

ID <- factor(pData.myoglu[ 1:52, 1])

design <- model.matrix(~ 0 + log2(VO2max) + Status + Time + ID)

Here is the design (not enough space to paste):

**38k**• written 3.5 years ago by Sindre •

**70**

It would be more concise and helpful to show us the three factors rather than the design matrix:

38kHere is data.frame(Status,Time,ID):

70