Evidence map›Paper›PMID 21118192›Full record

ArticleAnnals of human genetics2011

Importance measures for epistatic interactions in case-parent trios.

Holger Schwender, Katherine Bowers, M Daniele Fallin, Ingo Ruczinski

Abstract read
In one paragraph

Article in Annals of human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Bio-collections in autism research.Molecular autism · 2017
    Review
  5. Article
  6. Article
  7. 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.

Holger SchwenderDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21218, USA.
Katherine Bowers
M Daniele Fallin
Ingo Ruczinski

Funding

Novel Statistical Methods for Gene-Environment Interactions in Complex DiseasesR01HL090577 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI RUCZINSKI, INGO · 2007 to 2009
$1.1M
NCBDD CDC HHS U10 DD000183NHLBI NIH HHS R01 HL090577
6 · The paper itself

Abstract

Ensemble methods (such as Bagging and Random Forests) take advantage of unstable base learners (such as decision trees) to improve predictions, and offer measures of variable importance useful for variable selection. LogicFS has been proposed as such an ensemble learner for case-control studies when interactions of single nucleotide polymorphisms (SNPs) are of particular interest. LogicFS uses bootstrap samples of the data and employs the Boolean trees derived in logic regression as base learners to create ensembles of models that allow for the quantification of the contributions of epistatic interactions to the disease risk. In this article, we propose an extension of logicFS suitable for case-parent trio data, and derive an additional importance measure that is much less influenced by linkage disequilibrium between SNPs than the measure originally used in logicFS. We illustrate the performance of the novel procedure in simulation studies and in a case study of 461 case-parent trios with autistic children.

Indexed as

Epistasis, GeneticGenetic Predisposition to DiseasePolymorphism, Single NucleotideAutistic DisorderCase-Control StudiesFamilyFemaleHumansLinkage DisequilibriumMaleModels, Genetic

Identifiers

PMID21118192
PMCPMC3059247

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Registered trials

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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.