Abstract:
BACKGROUND:Many genome-wide collections of candidate cis-regulatory elements (cCREs) have been defined using genomic and epigenomic data, but it remains a major challenge to connect these elements to their target genes. RESULTS:To facilitate the development of computational methods for predicting target genes, we develop a Benchmark of candidate Enhancer-Gene Interactions (BENGI) by integrating the recently developed Registry of cCREs with experimentally derived genomic interactions. We use BENGI to test several published computational methods for linking enhancers with genes, including signal correlation and the TargetFinder and PEP supervised learning methods. We find that while TargetFinder is the best-performing method, it is only modestly better than a baseline distance method for most benchmark datasets when trained and tested with the same cell type and that TargetFinder often does not outperform the distance method when applied across cell types. CONCLUSIONS:Our results suggest that current computational methods need to be improved and that BENGI presents a useful framework for method development and testing.
journal_name
Genome Bioljournal_title
Genome biologyauthors
Moore JE,Pratt HE,Purcaro MJ,Weng Zdoi
10.1186/s13059-019-1924-8subject
Has Abstractpub_date
2020-01-22 00:00:00pages
17issue
1eissn
1474-7596issn
1474-760Xpii
10.1186/s13059-019-1924-8journal_volume
21pub_type
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