FASTmC：用于基于非参考的DNA甲基化估计的一套预测模型。
FASTmC: A Suite of Predictive Models for Nonreference-Based Estimations of DNA Methylation.
作者信息
Bewick Adam J, Hofmeister Brigitte T, Lee Kevin, Zhang Xiaoyu, Hall David W, Schmitz Robert J
机构信息
Department of Genetics, University of Georgia, Athens, Georgia 30602.
Institute of Bioinformatics, University of Georgia, Athens, Georgia 30602.
出版信息
G3 (Bethesda). 2015 Dec 17;6(2):447-52. doi: 10.1534/g3.115.025668.
We describe a suite of predictive models, coined FAST(m)C, for nonreference, 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.
我们描述了一套名为FAST(m)C的预测模型，用于对特定背景下的DNA甲基化水平进行无参考、经济高效的探索和比较分析。从全基因组亚硫酸氢盐测序产生的仅几千条短读段中就能获得对真实DNA甲基化水平的准确估计。这些模型使高分辨率时间进程或发育以及多样性研究变得切实可行，而无需考虑物种、基因组大小和参考基因组的可用性。
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