Evidence map›Paper›PMID 34648033›Full record

ArticleNucleic acids research2022

Prioritization of regulatory variants with tissue-specific function in the non-coding regions of human genome.

Shengcheng Dong, Alan P Boyle

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Genetic Variations in the Fibronectin 1 Gene (International journal of molecular sciences · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Challenges in screening forHGG advances · 2023
    Article
  11. Article
  12. Review
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Shengcheng DongDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Alan P BoyleDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-2081-1105
University of Michigan · US

Funding

RegulomeDB: A Resource for the Human RegulomeU24HG009293 · NHGRI · STANFORD UNIVERSITY · PI BOYLE, ALAN P, CHERRY, J. MICHAEL · 2020 to 2024
$3.3M
NHGRI NIH HHS U24 HG009293
6 · The paper itself

Abstract

Understanding the functional consequences of genetic variation in the non-coding regions of the human genome remains a challenge. We introduce h ere a computational tool, TURF, to prioritize regulatory variants with tissue-specific function by leveraging evidence from functional genomics experiments, including over 3000 functional genomics datasets from the ENCODE project provided in the RegulomeDB database. TURF is able to generate prediction scores at both organism and tissue/organ-specific levels for any non-coding variant on the genome. We present that TURF has an overall top performance in prediction by using validated variants from MPRA experiments. We also demonstrate how TURF can pick out the regulatory variants with tissue-specific function over a candidate list from associate studies. Furthermore, we found that various GWAS traits showed the enrichment of regulatory variants predicted by TURF scores in the trait-relevant organs, which indicates that these variants can be a valuable source for future studies.

Indexed as

Genome, HumanSoftwareCell LineData AnalysisGenomicsHumans

Identifiers

PMID34648033
PMCPMC8754628
OpenAlexW3206097003

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.