Integrative analysis of 111 reference human epigenomes
Integrative analysis of 111 reference human epigenomes is a dataset published in Nature (2015). On theSindex it has a DataRank of 14.8, placing it in the top 13% of the data-sharing corpus. It has been cited 7,079 times, with 172 citing works in its 1-hop citation network. Its calibrated FAIR score is 84/100.
Abstract
The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
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FAIR Checklist
Context only (not used in score)- Has DOI
- Indexed in repositories
- Open Access
- DataCite relations
- Linked datasets
- Dataset classification
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
DataRank Breakdown
Base Score Contribution
1.3
From this paper's citation signal
Citation Network Contribution
13.5
From 172 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- Fast and accurate short read alignment with Burrows–Wheeler transformBioinformatics200962,117 citationsDataRank 1.7
- Model-based Analysis of ChIP-Seq (MACS)Genome Biology200819,654 citationsDataRank 1.5
- An integrated encyclopedia of DNA elements in the human genomeNature201219,311 citationsDataRank 23.8Top 3%
- Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seqScience20165,121 citationsDataRank 1.3
- GREAT improves functional interpretation of cis-regulatory regionsNature Biotechnology20104,958 citationsDataRank 1.3
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 9% comes from its base citations and 91% from the citation network (172 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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