Evidence map›Paper›PMID 41676370›Full record

ArticleQuantitative biology (Beijing, China)2024

SimHOEPI: A resampling simulator for generating single nucleotide polymorphism data with a high-order epistasis model.

Yahan Li, Xinrui Cai, Junliang Shang, Yuanyuan Zhang, Jin-Xing Liu

Abstract read
In one paragraph

Article in Quantitative biology (Beijing, China), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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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

5 authors.

Yahan LiSchool of Computer Science Qufu Normal University Rizhao China.
Xinrui CaiSchool of Computer Science Qufu Normal University Rizhao China.
Junliang ShangSchool of Computer Science Qufu Normal University Rizhao China.
Yuanyuan ZhangSchool of Information and Control Engineering Qingdao University of Technology Qingdao China.
Jin-Xing LiuSchool of Health and Life Sciences University of Health and Rehabilitation Sciences Qingdao China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epistasis is a ubiquitous phenomenon in genetics, and is considered to be one of main factors in current efforts to unveil missing heritability of complex diseases. Simulation data is crucial for evaluating epistasis detection tools in genome-wide association studies (GWAS). Existing simulators normally suffer from two limitations: absence of support for high-order epistasis models containing multiple single nucleotide polymorphisms (SNPs), and inability to generate simulation SNP data independently. In this study, we proposed a simulator SimHOEPI, which is capable of calculating penetrance tables of high-order epistasis models depending on either prevalence or heritability, and uses a resampling strategy to generate simulation data independently. Highlights of SimHOEPI are the preservation of realistic minor allele frequencies in sampling data, the accurate calculation and embedding of high-order epistasis models, and acceptable simulation time. A series of experiments were carried out to verify these properties from different aspects. Experimental results show that SimHOEPI can generate simulation SNP data independently with high-order epistasis models, implying that it might be an alternative simulator for GWAS.

Indexed as

high‐order epistasis modelpenetrance tableresampling strategysimulationsingle nucleotide polymorphisms

Identifiers

PMID41676370
PMCPMC12806418

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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.