Evidence map›Paper›PMID 40448786›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Analysis of Genome-Wide Association Studies.

Piyush Gampawar, Edith Hofer, Nerea Alonso

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Piyush GampawarDivision of General Paediatrics, Medical University of Graz, Graz, Austria.
Edith HoferDepartment of Neurology, Medical University of Graz, Graz, Austria.
Nerea AlonsoClinical Institute for Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria. n.alonso@medunigraz.at.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) aim to identify genetic variants across the whole genome associated with the phenotype of interest. This technique has been largely used in the bone field to elucidate the genetic architecture of complex traits, like bone mineral density or fracture risk, and to date, more than 600 loci have been identified. To ensure that the associations are reliable, a careful design is required, depending upon the phenotype and the sample size, as well as the implementation of adequate quality control measures at both variant and sample levels. There is several software freely available to perform these studies, and different approaches can help increase the number of analyzed genetic variants, like imputation, or the sample size (meta-analysis). Further post-GWAS analysis can be applied to investigate the possible biological function and potential therapeutic relevance of the identified loci.

Indexed as

Genome-Wide Association StudyGenetic Predisposition to DiseaseHumansPhenotypePolymorphism, Single NucleotideSoftwareBioinformaticsGWASMeta-analysisQuality controlSNPs

Identifiers

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.