If you have normalised Beta values, and you trust the normalisation method (i.e. there's no way to get the IDAT files), then you can simply read that into R, convert to M values:
m <- log2(beta/(1 - beta))
Then perform a differential methylation analysis using Limma
As a warning, this code that I wrote may be slightly outdated.
However, if you have the raw .idats (which I think is important: if possible, I think testing different normalizations can give you a better feel for the robustness of your results), I think this code using a benchmark (described here) with some methods may also help as a starting point?
Otherwise, I think RnBeads has some good tutorials: