Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2020). On theSindex it has a DataRank of 0.998. It has been cited 22 times, with 16 citing works in its 1-hop citation network.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.470
From this paper's citation signal
Citation Network Contribution
0.528
From 12 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 16 citers.
National Institutes of Health
Grant: 5DP5OD024582-02
Identifying disease-relevant cell types by integrating genetic and functional genomics data
Fields of Study
Keywords
Sustainable Development Goals