Evidence map›Paper›PMID 23657481›Full record

ReviewNature reviews. Genetics2013

Meta-analysis methods for genome-wide association studies and beyond.

Evangelos Evangelou, John P A Ioannidis

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 340 papers, 55 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
340citing papers in PubMed, 55 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

340 citing papers in PubMed, 55 syntheses or guidelines pooled it.

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  16. Sequence-based GWAS meta-analyses for beef production traits.Genetics, selection, evolution : GSE · 2023
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280 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

2 authors.

Evangelos EvangelouClinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina 45110, Greece.
John P A Ioannidis

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meta-analysis of genome-wide association studies (GWASs) has become a popular method for discovering genetic risk variants. Here, we overview both widely applied and newer statistical methods for GWAS meta-analysis, including issues of interpretation and assessment of sources of heterogeneity. We also discuss extensions of these meta-analysis methods to complex data. Where possible, we provide guidelines for researchers who are planning to use these methods. Furthermore, we address special issues that may arise for meta-analysis of sequencing data and rare variants. Finally, we discuss challenges and solutions surrounding the goals of making meta-analysis data publicly available and building powerful consortia.

Indexed as

Meta-Analysis as TopicBayes TheoremData Interpretation, StatisticalGenetic HeterogeneityGenome-Wide Association StudyHumansPhenotypeSoftware

Identifiers

PMID23657481

What OpenQuestion holds

Textmetadata
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.