FASTmC: predictive models for non-reference-based estimations of DNA methylation

We describe a suite of predictive models, coined FASTmC, for non-reference, cost-effective exploration and comparative analysis of context-specific DNA methylation levels. Accurate estimations of true DNA methylation levels can be obtained from as few as several thousand short-reads generated from whole genome bisulfite sequencing. Our models make high-resolution time course or developmental, and large diversity studies practical regardless of species, genome size and availability of a reference genome. MethylC-Seq data collected from genomic DNA extracted from leaf tissue.