Evidence map›Paper›PMID 27939749›Full record

ReviewTrends in genetics : TIG2017

Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms.

Sierra S Nishizaki, Alan P Boyle

Abstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
–field-weighted citation impact
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

59 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Targeting PSAT1 to mitigate metastasis in tumors with p53-72Pro variant.Signal transduction and targeted therapy · 2023
    Article
  8. Potential biomarkers inBioinformation · 2023
    Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Using CRISPR to understand and manipulate gene regulation.Development (Cambridge, England) · 2021
    Review
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.

Sierra S NishizakiDepartment of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
Alan P BoyleDepartment of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: apboyle@umich.edu.

Funding

University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
Resource Informatics and ProductionU41HG009293 · NHGRI · STANFORD UNIVERSITY · PI BOYLE, ALAN P, CHERRY, J. MICHAEL · 2017 to 2019
$2.2M
Global Discovery and Validation of Functional Regulatory ElementsR00HG007356 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOYLE, ALAN P · 2014 to 2017
$776k
NHGRI NIH HHS R00 HG007356NHGRI NIH HHS T32 HG000040NHGRI NIH HHS U41 HG009293
6 · The paper itself

Abstract

One of the formative goals of genetics research is to understand how genetic variation leads to phenotypic differences and human disease. Genome-wide association studies (GWASs) bring us closer to this goal by linking variation with disease faster than ever before. Despite this, GWASs alone are unable to pinpoint disease-causing single nucleotide polymorphisms (SNPs). Noncoding SNPs, which represent the majority of GWAS SNPs, present a particular challenge. To address this challenge, an array of computational tools designed to prioritize and predict the function of noncoding GWAS SNPs have been developed. However, fewer than 40% of GWAS publications from 2015 utilized these tools. We discuss several leading methods for annotating noncoding variants and how they can be integrated into research pipelines in hopes that they will be broadly applied in future GWAS analyses.

Indexed as

Computational BiologyGenome-Wide Association StudyGenetic Predisposition to DiseaseHumansMolecular Sequence AnnotationPolymorphism, Single NucleotideRegulatory Sequences, Nucleic Acid

Identifiers

PMID27939749
PMCPMC5553318

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.