FASTmC: A Suite of Predictive Models for Nonreference-Based Estimations of DNA Methylation | Zendy

Adam J. Bewick | Zendy; Brigitte T. Hofmeister | Zendy; Kevin Lee | Zendy; Xiaoyu Zhang | Zendy; David W. Hall | Zendy; Robert J. Schmitz | Zendy

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FASTmC: A Suite of Predictive Models for Nonreference-Based Estimations of DNA Methylation

Author(s) -

Adam J. Bewick,

Brigitte T. Hofmeister,

Kevin Lee,

Xiaoyu Zhang,

David W. Hall,

Robert J. Schmitz

Publication year - 2015

Publication title -

g3 genes genomes genetics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.468

H-Index - 66

ISSN - 2160-1836

DOI - 10.1534/g3.115.025668

Subject(s) - dna methylation , genome , computational biology , context (archaeology) , bisulfite , bisulfite sequencing , methylation , biology , suite , dna sequencing , reference genome , computer science , dna , genetics , gene , geography , gene expression , archaeology , paleontology

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.

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