Evidence map›Paper›PMID 29246109›Full record

SynthesisBMC bioinformatics2017

MetaGenyo: a web tool for meta-analysis of genetic association studies.

Jordi Martorell-Marugan, Daniel Toro-Dominguez, Marta E Alarcon-Riquelme, Pedro Carmona-Saez

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 43 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 43 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

70 citing papers in PubMed, 43 syntheses or guidelines pooled it.

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  3. Association BetweenInternational journal of environmental research and public health · 2026
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  4. Comprehensive Meta-Analysis on the Impact of theCurrent pharmaceutical design · 2026
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  8. NewbornGenes · 2025
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  14. Association ofFrontiers in immunology · 2025
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  15. Role of theInternational journal of environmental research and public health · 2024
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10 more citing papers are in PubMed but not listed here.

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.

Jordi Martorell-MaruganBioinformatics Unit, Centre for Genomics and Oncological Research (GENYO), Granada, Spain.
Daniel Toro-DominguezBioinformatics Unit, Centre for Genomics and Oncological Research (GENYO), Granada, Spain.
Marta E Alarcon-RiquelmeMedical Genomics, Centre for Genomics and Oncological Research (GENYO), Granada, Spain.
Pedro Carmona-SaezBioinformatics Unit, Centre for Genomics and Oncological Research (GENYO), Granada, Spain. pedro.carmona@genyo.es.ORCID http://orcid.org/0000-0002-6173-7255

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetic association studies (GAS) aims to evaluate the association between genetic variants and phenotypes. In the last few years, the number of this type of study has increased exponentially, but the results are not always reproducible due to experimental designs, low sample sizes and other methodological errors. In this field, meta-analysis techniques are becoming very popular tools to combine results across studies to increase statistical power and to resolve discrepancies in genetic association studies. A meta-analysis summarizes research findings, increases statistical power and enables the identification of genuine associations between genotypes and phenotypes. Meta-analysis techniques are increasingly used in GAS, but it is also increasing the amount of published meta-analysis containing different errors. Although there are several software packages that implement meta-analysis, none of them are specifically designed for genetic association studies and in most cases their use requires advanced programming or scripting expertise.

resultsWe have developed MetaGenyo, a web tool for meta-analysis in GAS. MetaGenyo implements a complete and comprehensive workflow that can be executed in an easy-to-use environment without programming knowledge. MetaGenyo has been developed to guide users through the main steps of a GAS meta-analysis, covering Hardy-Weinberg test, statistical association for different genetic models, analysis of heterogeneity, testing for publication bias, subgroup analysis and robustness testing of the results.

conclusionsMetaGenyo is a useful tool to conduct comprehensive genetic association meta-analysis. The application is freely available at http://bioinfo.genyo.es/metagenyo/ .

Indexed as

InternetSoftwareGenetic Association StudiesHumansMetagenomicsGenetic association studyMeta-analysisShinyWeb tool

Identifiers

PMID29246109
PMCPMC5732412

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.