Evidence map›Paper›PMID 22973544›Full record

ArticleG3 (Bethesda, Md.)2012

Uncovering networks from genome-wide association studies via circular genomic permutation.

Claudia P Cabrera, Pau Navarro, Jennifer E Huffman, Alan F Wright, Caroline Hayward, Harry Campbell, James F Wilson, Igor Rudan, Nicholas D Hastie, Veronique Vitart and 1 more

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

11 authors.

Claudia P CabreraMRC Human Genetics Unit, Medical Research Council, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, Scotland, United Kingdom. Claudia.Cabrera@ed.ac.uk
Pau Navarro
Jennifer E Huffman
Alan F Wright
Caroline Hayward
Harry Campbell
James F Wilson
Igor Rudan
Nicholas D Hastie
Veronique Vitart
Chris S Haley

Funding

Biotechnology and Biological Sciences Research CouncilChief Scientist Office CZB/4/710Medical Research Council MC_PC_U127561128Medical Research Council MC_PC_U127592696Medical Research Council MC_U127561128Medical Research Council MC_U127592696
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) aim to detect single nucleotide polymorphisms (SNP) associated with trait variation. However, due to the large number of tests, standard analysis techniques impose highly stringent significance thresholds, leaving potentially associated SNPs undetected, and much of the trait genetic variation unexplained. Pathway- and network-based methodologies applied to GWAS aim to detect associations missed by standard single-marker approaches. The complex and non-random architecture of the genome makes it a challenge to derive an appropriate testing framework for such methodologies. We developed a rapid and simple permutation approach that uses GWAS SNP association results to establish the significance of pathway associations while accounting for the linkage disequilibrium structure of SNPs and the clustering of functionally related elements in the genome. All SNPs used in the GWAS are placed in a "circular genome" according to their location. Then the complete set of SNP association P values are permuted by rotation with respect to the genomic locations of the SNPs. Once these "simulated" P values are assigned, the joint gene P values are calculated using Fisher's combination test, and the association of pathways is tested using the hypergeometric test. The circular genomic permutation approach was applied to a human genome-wide association dataset. The data consists of 719 individuals from the ORCADES study genotyped for ~300,000 SNPs and measured for 51 traits ranging from physical to biochemical measurements. KEGG pathways (n = 225) were used as the sets of pathways to be tested. Our results demonstrate that the circular genomic permutations provide robust association P values. The non-permuted hypergeometric analysis generates ~1400 pathway-trait combination results with an association P value more significant than P ≤ 0.05, whereas applying circular genomic permutation reduces the number of significant results to a more credible 40% of that value. The circular permutation software ("genomicper") is available as an R package at http://cran.r-project.org/.

Indexed as

Gene Regulatory NetworksGenome, HumanGenome-Wide Association StudyPolymorphism, Single NucleotideSignal TransductionCardiomyopathiesComputer SimulationGenomicsHumansInternetModels, GeneticMolecular Sequence AnnotationSoftwarecardiac diseasegenomicper R packageGWASpathway-basedpermutation method

Identifiers

PMID22973544
PMCPMC3429921

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Registered trials

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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.