This turns out to be more and more of a problem. When we first designed methylKit it was tested on RRBS data with couple of million CpGs covered. These days many people have either many RRBS or similar reduced representation sequencing results or a fair amount whole-genome bisulfite sequencing. Due to their size, it may be difficult to work with these kind of samples in-memory. We developed a flatfile database based on "tabix"(http://www.htslib.org/doc/tabix.html). This means large objects are written out as tabix files, they are compressed and indexed. We can work with them chunk-by-chunk in a parallelized manner. However, that comes with a cost. It will take time to initially create tabix files but you will be able to work with large data sets without so much of the memory bottleneck.
Bismark aligner scripts can produce per base methylation files. These files, namely "cytosine report" and "coverage" files can be read in R using methylKit methRead() function. See Bismark manual for details on the files.
Great release and will try it out extensively in the next few days!
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