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

## TL;DR

FASTmC is a tool that estimates DNA methylation levels without needing a reference genome, making large-scale studies more accessible.

## Contribution

FASTmC introduces a novel suite of predictive models for non-reference-based DNA methylation estimation.

## Key findings

- FASTmC can estimate DNA methylation levels from as few as several thousand short-reads.
- The models work across species and genome sizes without needing a reference genome.

## Abstract

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. These models make high-resolution time course or developmental, and large diversity studies practical regardless of species, genome size and availability of a reference genome.