My data are log2 fold changes (FCs) between control and treatment usually coming from triple replicated affymetrix microarrays. I also have p-values for those data determined by t-test. As I currently have only those data available and not the replicates themselves, I wonder if it is sensible to use the FCs as input for the limma function `lmFit`

?

The results I get seem reasonable but I have found no way to include the p-value information which makes me uneasy about the reliability. Is this possible in some way or is my only solution to obtain the raw replicate data?

Thank you for your insights.

The data are from treatment experiments that have a dose and time dependency, so that I just fit a linear model to the FC as a function of time and dose. However, the lack of variability and significance information of the FCs is a big concern to me, too, so I'll try to obtain the raw data, I suppose.