Evidence map›Paper›PMID 36553553›Full record

ArticleGenes2022

EpiReSIM: A Resampling Method of Epistatic Model without Marginal Effects Using Under-Determined System of Equations.

Junliang Shang, Xinrui Cai, Tongdui Zhang, Yan Sun, Yuanyuan Zhang, Jinxing Liu, Boxin Guan

Abstract read
In one paragraph

Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

7 authors.

Junliang ShangSchool of Computer Science, Qufu Normal University, Rizhao 276826, China.ORCID 0000-0002-8488-2228
Xinrui CaiSchool of Computer Science, Qufu Normal University, Rizhao 276826, China.ORCID 0000-0003-3260-7133
Tongdui ZhangScience and Technology Innovation Service Institution of Rizhao, Rizhao 276827, China.
Yan SunSchool of Computer Science, Qufu Normal University, Rizhao 276826, China.
Yuanyuan ZhangSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China.
Jinxing LiuSchool of Computer Science, Qufu Normal University, Rizhao 276826, China.
Boxin GuanSchool of Computer Science, Qufu Normal University, Rizhao 276826, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation experiments are essential to evaluate epistasis detection methods, which is the main way to prove their effectiveness and move toward practical applications. However, due to the lack of effective simulators, especially for simulating models without marginal effects (eNME models), epistasis detection methods can hardly verify their effectiveness through simulation experiments. In this study, we propose a resampling simulation method (EpiReSIM) for generating the eNME model. First, EpiReSIM provides two strategies for solving eNME models. One is to calculate eNME models using prevalence constraints, and another is by joint constraints of prevalence and heritability. We transform the computation of the model into the problem of solving the under-determined system of equations. Introducing the complete orthogonal decomposition method and Newton's method, EpiReSIM calculates the solution of the underdetermined system of equations to obtain the eNME model, especially the solution of the high-order model, which is the highlight of EpiReSIM. Second, based on the computed eNME model, EpiReSIM generates simulation data by a resampling method. Experimental results show that EpiReSIM has advantages in preserving the biological properties of minor allele frequencies and calculating high-order models, and it is a convenient and effective alternative method for current simulation software.

Indexed as

Epistasis, GeneticSoftwareComputer Simulationepistasis modelGWASheritabilitypenetrance tableprevalenceresamplingsimulation

Identifiers

PMID36553553
PMCPMC9777644

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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.