Evidence map›Paper›PMID 35061909›Full record

ArticleNucleic acids research2022

Polympact: exploring functional relations among common human genetic variants.

Samuel Valentini, Francesco Gandolfi, Mattia Carolo, Davide Dalfovo, Lara Pozza, Alessandro Romanel

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 37% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Samuel ValentiniDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
Francesco GandolfiDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
Mattia CaroloDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
Davide DalfovoDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
Lara PozzaDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
Alessandro RomanelDepartment of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.ORCID 0000-0003-4855-8620
University of Trento · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants' interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants' functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.

Indexed as

Genome-Wide Association StudyHuman GeneticsCluster AnalysisHumansPolymorphism, Single Nucleotide

Identifiers

PMID35061909
PMCPMC8860573
OpenAlexW4206255826

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.