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学術論文

Accurate promoter and enhancer identification in 127 ENCODE and roadmap epigenomics cell types and tissues by GenoSTAN.

MPS-Authors
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Michel,  M.
Department of Molecular Biology, MPI for Biophysical Chemistry, Max Planck Society;

/persons/resource/persons173057

Schwalb,  B.
Department of Molecular Biology, MPI for Biophysical Chemistry, Max Planck Society;

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Cramer,  P.
Department of Molecular Biology, MPI for Biophysical Chemistry, Max Planck Society;

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フルテキスト (公開)

2380733.pdf
(出版社版), 6MB

付随資料 (公開)

2380733_Suppl.htm
(付録資料), 274KB

引用

Zacher, B., Michel, M., Schwalb, B., Cramer, P., Tresch, A., & Gagneur, J. (2017). Accurate promoter and enhancer identification in 127 ENCODE and roadmap epigenomics cell types and tissues by GenoSTAN. PLoS One, 12(1):. doi:10.1371/journal.pone.0169249.


引用: http://hdl.handle.net/11858/00-001M-0000-002C-3517-B
要旨
Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today’s largest compendium of chromatin assays. Extensive benchmarks demonstrate that GenoSTAN generally identifies promoters and enhancers with significantly higher accuracy than previous methods. Moreover, GenoSTAN-derived promoters and enhancers showed significantly higher enrichment of complex trait-associated genetic variants than current annotations. Altogether, GenoSTAN provides an easy-to-use tool to define promoters and enhancers in any system, and our annotation of human transcriptional cis-regulatory elements constitutes a rich resource for future research in biology and medicine.