Evidence map›Paper›PMID 34788792›Full record

ArticleBioinformatics (Oxford, England)2022

GADGETS: a genetic algorithm for detecting epistasis using nuclear families.

Michael Nodzenski, Min Shi, Juno M Krahn, Alison S Wise, Yuanyuan Li, Leping Li, David M Umbach, Clarice R Weinberg

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

Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 60% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Michael NodzenskiBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.ORCID 0000-0001-5476-8427
Min ShiBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.ORCID 0000-0001-8265-5307
Juno M KrahnGenome Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.
Alison S WiseBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.
Yuanyuan LiBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.
Leping LiBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.ORCID 0000-0003-4208-0259
David M UmbachBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.ORCID 0000-0002-7142-2812
Clarice R WeinbergBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.
National Institute of Environmental Health Sciences · US

Funding

Statistical Methods For Genetic EpidemiologyZIAES040007 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 2009 to 2025
$6.5M
Statistical Methods For Gene/environment Interaction And Genetic SusceptibilityZIAES045002 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI UMBACH, DAVID M · 2009 to 2025
$830k
STATISTICAL METHODS IN REPRODUCTIVE EPIDEMIOLOGYZ01ES040007 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 1997 to 2008
$512k
Intramural NIH HHS Z01 ES040007
6 · The paper itself

Abstract

motivationEpistasis may play an etiologic role in complex diseases, but research has been hindered because identification of interactions among sets of single nucleotide polymorphisms (SNPs) requires exploration of immense search spaces. Current approaches using nuclear families accommodate at most several hundred candidate SNPs.

resultsGADGETS detects epistatic SNP-sets by applying a genetic algorithm to case-parent or case-sibling data. To allow for multiple epistatic sets, island subpopulations of SNP-sets evolve separately under selection for evident joint relevance to disease risk. The software evaluates the identified SNP-sets via permutation testing and provides graphical visualization. GADGETS correctly identified epistatic SNP-sets in realistically simulated case-parent triads with 10 000 candidate SNPs, far more SNPs than competitors can handle, and it outperformed competitors in simulations with many fewer SNPs. Applying GADGETS to family-based oral-clefting data from dbGaP identified SNP-sets with possible epistatic effects on risk. AVAILABILITY AND IMPLEMENTATION: GADGETS is part of the epistasisGA package at https://github.com/mnodzenski/epistasisGA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsEpistasis, GeneticGenome-Wide Association StudyHumansNuclear FamilyPolymorphism, Single NucleotideSoftware

Identifiers

PMID34788792
PMCPMC10060691
OpenAlexW3212362400

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.