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Genome Biol. 2018 May 1;19(1):56. doi: 10.1186/s13059-018-1432-2.

FOCS: a novel method for analyzing enhancer and gene activity patterns infers an extensive enhancer-promoter map.

Author information

1
Blavatnik School of Computer Science, Tel Aviv University, 69978, Tel Aviv, Israel.
2
Department of Human Molecular Genetics & Biochemistry, Sackler School of Medicine, Tel Aviv University, 69978, Tel Aviv, Israel.
3
Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, 94305, USA.
4
Blavatnik School of Computer Science, Tel Aviv University, 69978, Tel Aviv, Israel. rshamir@tau.ac.il.
5
Department of Human Molecular Genetics & Biochemistry, Sackler School of Medicine, Tel Aviv University, 69978, Tel Aviv, Israel. ranel@tauex.tau.ac.il.
6
Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel. ranel@tauex.tau.ac.il.

Abstract

Recent sequencing technologies enable joint quantification of promoters and their enhancer regions, allowing inference of enhancer-promoter links. We show that current enhancer-promoter inference methods produce a high rate of false positive links. We introduce FOCS, a new inference method, and by benchmarking against ChIA-PET, HiChIP, and eQTL data show that it results in lower false discovery rates and at the same time higher inference power. By applying FOCS to 2630 samples taken from ENCODE, Roadmap Epigenomics, FANTOM5, and a new compendium of GRO-seq samples, we provide extensive enhancer-promotor maps ( http://acgt.cs.tau.ac.il/focs ). We illustrate the usability of our maps for deriving biological hypotheses.

KEYWORDS:

ChIA-PET; ENCODE; Enhancers; FANTOM5; GRO-seq; Gene regulation; Promoters; Roadmap; eQTL; eRNA

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