As already pointed out, the normal DESeq2 log2FC are shrunken. For this reason, the program doesn't show the two basemeans, since the default log2FC wouldn't match. If you want to know these values, you'll need to get the MLE log2FC, by setting the option
addMLE = TRUE when calling the function
results(). You can access all intermediate quantities computed by DESeq2 with the function
mcols(dds) on the DESeqDataSet object. There you'll find
MLE_Intercept column and
MLE_contrast_B_vs_A. In case you have a simple single variable design, your first condition basemean will simply be
2^MLE_Intercept and the second condition basemean is
2^(MLE_Intercept + MLE_contrast_B_vs_A). The general basemean, reported in the results, would be the average of the two.
Since DESeq2 shrinks fold-changes I'm not sure how well basemeanB would match what you're expecting. Anyway, "basemean" is essentially the intercept in the GLM, with the caveat that an "extended model matrix" might get used in which case it's more like what you'd get with a
~1 design. The log2foldchanges are then the equivalent coefficients from the GLM. Note that these are shrunken by default, which tends to make them more reliable (so you're not going to calculate them by hand).