Spearman dependence function-based goodness-of-fit test for the gene's relation

A gene network represents the relationship between different groups of genes with various functions, aiming to depict how genes collaborate and influence each other's activities within a biological system. This relationship can be effectively explained using copulas. Therefore, it is crucial to determine which copula best fits the gene data and provide the most accurate explanation of the relationships between gene groups. In this study, our objective is to introduce a Spearman dependence function-based goodness-of-fit test using Bernstein polynomial approximation. We apply this test to identify a copula model that can effectively explain the relationships between gene groups. A Monte Carlo simulation study is conducted to assess the performance of the proposed test. Next, we analyse histone gene groups using data from yeast cell regulation, as provided by Eisen et al. (1998). Specifically, we investigate the dependence model structures of gene interactions for eight histone genes.

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Publication Details

Journal
International Journal of Data Mining and Bioinformatics
Published
2024-12-03
DOI
https://doi.org/10.1504/ijdmb.2025.142968
Citations
1
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.23
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article

Spearman dependence function-based goodness-of-fit test for the gene's relation

Burcu Hüdaverdi, Selim Orhun Susam
1 citations
International Journal of Data Mining and Bioinformatics
Gene expression and cancer classification
0.23
article

Spearman dependence function-based goodness-of-fit test for the gene's relation

Burcu Hüdaverdi, Selim Orhun Susam
article en
1 citations

Abstract

A gene network represents the relationship between different groups of genes with various functions, aiming to depict how genes collaborate and influence each other's activities within a biological system. This relationship can be effectively explained using copulas. Therefore, it is crucial to determine which copula best fits the gene data and provide the most accurate explanation of the relationships between gene groups. In this study, our objective is to introduce a Spearman dependence function-based goodness-of-fit test using Bernstein polynomial approximation. We apply this test to identify a copula model that can effectively explain the relationships between gene groups. A Monte Carlo simulation study is conducted to assess the performance of the proposed test. Next, we analyse histone gene groups using data from yeast cell regulation, as provided by Eisen et al. (1998). Specifically, we investigate the dependence model structures of gene interactions for eight histone genes.

International Journal of Data Mining and BioinformaticsVol. 29(1/2)
Dokuz Eylül University (TR), Munzur University (TR)
Openalex Percentile: Top 40%
Gene expression and cancer classification
0.23
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