Evidence map›Paper›PMID 30389795›Full record

ArticleG3 (Bethesda, Md.)2018

vqtl: An R Package for Mean-Variance QTL Mapping.

Robert W Corty, William Valdar

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Bayesian matrix completion for hypothesis testing.Journal of the Royal Statistical Society. Series C, Applied statistics · 2023
    Article
  6. Genome-to-phenome research in rats: progress and perspectives.International journal of biological sciences · 2021
    Review
  7. Article
  8. Article
  9. 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

2 authors.

Robert W CortyDepartment of Genetics.ORCID 0000-0002-6787-9051
William ValdarDepartment of Genetics william.valdar@unc.edu.ORCID 0000-0002-2419-0430

Funding

Statistical Modeling of Multiparental and Genetic Reference PopulationsR35GM127000 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI William Valdar · 2018 to 2026
$3.1M
UNC Predoc Training Progr in Bioinformatics/Comp BiologyT32GM067553 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELSTON, TIMOTHY C · 2005 to 2019
$2.5M
Statistical Modeling of Complex Traits in Genetic Reference Super-PopulationsR01GM104125 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI VALDAR, WILLIAM · 2012 to 2016
$1.2M
Big Data to Knowledge Training ProgramT32LM012420 · NLM · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FOREST, MARK GREGORY, KOSOROK, MICHAEL R · 2016 to 2019
$1.1M
The interplay between genes and environment on cardiovascular disease phenotypesR21HL126045 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LANGE, ETHAN MATHER, LANGE, LESLIE A · 2015 to 2016
$447k
Statistical modeling of genetic effects on behavior and its variabilityF30MH108265 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CORTY, ROBERT WALLACE · 2016 to 2018
$119k
NHLBI NIH HHS R21 HL126045NIGMS NIH HHS R01 GM104125NIGMS NIH HHS R35 GM127000NIGMS NIH HHS T32 GM067553NIMH NIH HHS F30 MH108265NLM NIH HHS T32 LM012420
6 · The paper itself

Abstract

We present vqtl, an R package for mean-variance QTL mapping. This QTL mapping approach tests for genetic loci that influence the mean of the phenotype, termed mean QTL, the variance of the phenotype, termed variance QTL, or some combination of the two, termed mean-variance QTL. It is unique in its ability to correct for variance heterogeneity arising not only from the QTL itself but also from nuisance factors, such as sex, batch, or housing. This package provides functions to conduct genome scans, run permutations to assess the statistical significance, and make informative plots to communicate results. Because it is inter-operable with the popular qtl package and uses many of the same data structures and input patterns, it will be straightforward for geneticists to analyze future experiments with vqtl as well as re-analyze past experiments, possibly discovering new QTL.

Indexed as

GenomePhenotypeQuantitative Trait, HeritableSoftwareDGLMheteroscedastic regression, mvQTLvariance heterogeneity

Identifiers

PMID30389795
PMCPMC6288833

What OpenQuestion holds

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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.