Evidence map›Paper›PMID 30295862›Full record

ArticleThe Journal of heredity2018

The G-matrix Simulator Family: Software for Research and Teaching.

Adam G Jones, Reinhard Bürger, Stevan J Arnold

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of heredity, 2018. 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, top 94% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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 at 1 institution in 2 countries.

Adam G JonesDepartment of Biological Sciences, University of Idaho, Moscow, ID.
Reinhard BürgerFaculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz, Vienna, Austria.
Stevan J ArnoldDepartment of Integrative Biology, Oregon State University, Corvallis, OR.
University of Idaho · US

Funding

MODELING MULTIVARIATE SELECTION ON COMPLEX CHARACTERSF32GM020561 · NIGMS · OREGON STATE UNIVERSITY · PI JONES, ADAM G. · 2000 to 2001
$80k
NIGMS NIH HHS F32 GM020561
6 · The paper itself

Abstract

Genetic variation plays a fundamental role in all models of evolution. For phenotypes composed of multiple quantitative traits, genetic variation is best quantified as additive genetic variances and covariances, as these values determine the rate and trajectory of evolution. Additive genetic variances and covariances are often summarized conveniently in the G-matrix, which has additive genetic variances for each trait on the diagonal and additive genetic covariances as its off-diagonal elements. The evolution of the G-matrix is an interesting topic in its own right, because the processes that affect trait means also affect the distribution of standing genetic variation, which, in turn, feeds back to affect the rate of change of trait means. Theoretical studies of the G-matrix have profitably employed simulation-based models because the topic is often too complex to yield meaningful analytical results. Here, we present a series of G-matrix simulation software packages, which have emerged from about 15 years of research on this topic. These simulation models are useful for research and for building intuition regarding the evolution of the G-matrix under a wide variety of circumstances. A tutorial and source code also provide a foundation upon which future models can be built. These tools will be useful to students as well as researchers.

Indexed as

Genetic ResearchSoftwareTeachingEvolution, MolecularModels, Genetic

Identifiers

PMID30295862
PMCPMC6208455
OpenAlexW2895359359

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.