Evidence map›Paper›PMID 31430752›Full record

ArticleHuman heredity2019

The Contribution Plot: Decomposition and Graphical Display of the RV Coefficient, with Application to Genetic and Brain Imaging Biomarkers of Alzheimer's Disease.

JinCheol Choi, Donghuan Lu, Mirza Faisal Beg, Jinko Graham, Brad McNeney, for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Human heredity, 2019. 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 95% 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

6 authors at 1 institution in 1 country.

JinCheol ChoiDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Donghuan LuSchool of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Mirza Faisal BegSchool of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Jinko GrahamDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Brad McNeneyDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada, mcneney@sfu.ca.
for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Simon Fraser University · CA

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
PREDICT-ADFTD: Multimodal Imaging Prediction of AD/FTD and Differential DiagnosisR01AG055121 · NIA · OHIO STATE UNIVERSITY · PI ROSEN, HOWARD J, WANG, LEI · 2017 to 2020
$2.8M
NIA NIH HHS R01 AG055121NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

BACKGROUND/

aimsAlzheimer's disease (AD) is a chronic neurodegenerative disease that causes memory loss and a decline in cognitive abilities. AD is the sixth leading cause of death in the USA, affecting an estimated 5 million Americans. To assess the association between multiple genetic variants and multiple measurements of structural changes in the brain, a recent study of AD used a multivariate measure of linear dependence, the RV coefficient. The authors decomposed the RV coefficient into contributions from individual variants and displayed these contributions graphically.

methodsWe investigate the properties of such a "contribution plot" in terms of an underlying linear model, and discuss shrinkage estimation of the components of the plot when the correlation signal may be sparse.

resultsThe contribution plot is applied to simulated data and to genomic and brain imaging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

conclusionsThe contribution plot with shrinkage estimation can reveal truly associated explanatory variables.

Indexed as

NeuroimagingAlzheimer DiseaseApolipoproteins EBiomarkersBrainComputer SimulationGenotypeHumansPhenotypePolymorphism, Single NucleotideApolipoproteins EBiomarkersAlzheimer’s diseaseGraphical displayMultivariate correlationRV coefficientShrinkage estimation

Identifiers

PMID31430752
PMCPMC9008771
OpenAlexW2938734262

What OpenQuestion holds

Textmetadata
LicenceTDM
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.