Evidence map›Paper›PMID 33672535›Full record

SynthesisGenes2021

G2PMineR: A Genome to Phenome Literature Review Approach.

John M A Wojahn, Stephanie J Galla, Anthony E Melton, Sven Buerki

Abstract readMeta-Analysis
In one paragraph

Synthesis in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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.

John M A WojahnDepartment of Biological Sciences, Boise State University, Boise, ID 83725, USA.
Stephanie J GallaDepartment of Biological Sciences, Boise State University, Boise, ID 83725, USA.
Anthony E MeltonDepartment of Biological Sciences, Boise State University, Boise, ID 83725, USA.
Sven BuerkiDepartment of Biological Sciences, Boise State University, Boise, ID 83725, USA.ORCID 0000-0002-8299-6539

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a gap in the conceptual framework linking genes to phenotypes (G2P) for non-model organisms, as most non-model organisms do not yet have genomic resources readily available. To address this, researchers often perform literature reviews to understand G2P linkages by curating a list of likely gene candidates, hinging upon other studies already conducted in closely related systems. Sifting through hundreds to thousands of articles is a cumbersome task that slows down the scientific process and may introduce bias into a study. To fill this gap, we created G2PMineR, a free and open source literature mining tool developed specifically for G2P research. This R package uses automation to make the G2P review process efficient and unbiased, while also generating hypothesized associations between genes and phenotypes within a taxonomical framework. We applied the package to a literature review for drought-tolerance in plants. The analysis provides biologically meaningful results within the known framework of drought tolerance in plants. Overall, the package is useful for conducting literature reviews for genome to phenome projects, and also has broad appeal to scientists investigating a wide range of study systems as it can conduct analyses under the auspices of three different kingdoms (Plantae, Animalia, and Fungi).

Indexed as

Computational BiologyGenomeGenotypePhenotypeSoftwareAnimalsDatabases, GeneticData MiningGenomicsHumansPhenomicsPlantsWeb BrowserG2Pgenotypeliterature miningliterature reviewphenotype

Identifiers

PMID33672535
PMCPMC7923769

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.