Evidence map›Paper›PMID 41527909›Full record

ArticleG3 (Bethesda, Md.)2026

G2P datasets: a hub for genomic datasets for predictive modeling in plants and animals.

Fernando Aguate, Mark Watson, Harish Neelam, Yunxuan Deng, Jack Dekkers, Juan Pedro Steibel, Hao Cheng, Gustavo de Los Campos

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2026. 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

8 authors.

Fernando AguateDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, United States.ORCID 0000-0002-3608-8425
Mark WatsonStatistical and Quantitative Genetics, Department of Animal Science, University of California -Davis, Davis, CA 95616, United States.
Harish NeelamDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, United States.
Yunxuan DengStatistical and Quantitative Genetics, Department of Animal Science, University of California -Davis, Davis, CA 95616, United States.
Jack DekkersDepartment of Animal Science, Iowa State University, Ames, IA 50011, United States.ORCID 0000-0003-1557-7577
Juan Pedro SteibelDepartment of Animal Science, Iowa State University, Ames, IA 50011, United States.
Hao ChengStatistical and Quantitative Genetics, Department of Animal Science, University of California -Davis, Davis, CA 95616, United States.ORCID 0000-0001-5146-7231
Gustavo de Los CamposDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, United States.ORCID 0000-0001-5692-7129

Funding

National Institute of Food and Agriculture Competitive 2023-67015-39564National Institute of Food and Agriculture Competitive 2023-70412-41054USDA Agriculture and Food Research Initiative
6 · The paper itself

Abstract

We present G2P Datasets, a novel, open-access repository of publicly available genomic datasets for plants and animals. G2P Datasets currently hosts more than 100 public genomic datasets, meticulously compiled from diverse publications. The repository hosts meta-data (including digital object identifier for the hosted datasets) and scripts that can be used to download and read each dataset hosted into an R-environment. Scientists can submit new datasets by completing an online form. Additionally, many of the curated datasets are accessible through Kaggle and through links that allow rapid download of formatted R-objects. A searchable database of meta-data allows users to search through datasets for more than 60 species of plants and animals in a variety of traits and sample sizes. The repository is accessible via a web app interface with a catalog and clear instructions to contribute by adding new datasets and through GitHub. By unifying genomic and phenotypic meta-data into a navigable platform, we aim to facilitate genome-to-phenotype research in plant and animal genetics. This article provides an overview of the repository's content, organization, and utility.

Indexed as

Databases, GeneticGenomicsPlantsAnimalsBiocurationGenome, PlantPhenotypeSoftwareanimal breedingdata sharingFAIRgenomic predictiongenomic researchopen-access repositoryplant breedingSNP data

Identifiers

PMID41527909
PMCPMC13148407

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.