Evidence map›Paper›PMID 26110313›Full record

ArticleGenes2015

JAG: A Computational Tool to Evaluate the Role of Gene-Sets in Complex Traits.

Esther S Lips, Maarten Kooyman, Christiaan de Leeuw, Danielle Posthuma

Abstract read
In one paragraph

Article in Genes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Examination of the Involvement of Cholinergic-Associated Genes in Nicotine Behaviors in European and African Americans.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2017
    Article
  7. Article
  8. Article
  9. Article
  10. 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

4 authors.

Esther S LipsDepartment of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University & VU Medical Center, Amsterdam 1081HV, The Netherlands. e.s.lips@vu.nl.
Maarten KooymanNetherlands Bioinformatics Centre, Geert de Grooteplein 28, Nijmegen 6525 GA, The Netherlands. kooyman@gmail.com.
Christiaan de LeeuwDepartment of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University & VU Medical Center, Amsterdam 1081HV, The Netherlands. c.deleeuw@science.ru.nl.
Danielle PosthumaDepartment of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University & VU Medical Center, Amsterdam 1081HV, The Netherlands. d.posthuma@vu.nl.

Funding

Wellcome Trust 076113Wellcome Trust 085475
6 · The paper itself

Abstract

Gene-set analysis has been proposed as a powerful tool to deal with the highly polygenic architecture of complex traits, as well as with the small effect sizes typically found in GWAS studies for complex traits. We developed a tool, Joint Association of Genetic variants (JAG), which can be applied to Genome Wide Association (GWA) data and tests for the joint effect of all single nucleotide polymorphisms (SNPs) located in a user-specified set of genes or biological pathway. JAG assigns SNPs to genes and incorporates self-contained and/or competitive tests for gene-set analysis. JAG uses permutation to evaluate gene-set significance, which implicitly controls for linkage disequilibrium, sample size, gene size, the number of SNPs per gene and the number of genes in the gene-set. We conducted a power analysis using the Wellcome Trust Case Control Consortium (WTCCC) Crohn's disease data set and show that JAG correctly identifies validated gene-sets for Crohn's disease and has more power than currently available tools for gene-set analysis. JAG is a powerful, novel tool for gene-set analysis, and can be freely downloaded from the CTG Lab website.

Indexed as

biological pathwaygene-set analysisgenetic associationGWASpathway analysis

Identifiers

PMID26110313
PMCPMC4488663

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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.