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Gene selection in a single cell gene decision space based on class-consistent technology and fuzzy rough iterative computation model

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Abstract

This study explores gene selection in a single cell gene decision space (scgd-space) based on class-consistent technology and fuzzy rough iterative computation model (FRIC-model). Gene expression data (ge-data) exhibit characteristics such as limited sample size, high dimensionality, and noise. Due to their high dimensionality, gene selection must be carried out before clustering and classifying them. The existing gene selection methods based on equivalence relation are not effective for ge-data owing to the strictness of the equality between gene expression values. In order to overcome this weakness, class-consistent technology of replacing equality with approximate equality between gene expression values is first proposed. Then, “the class consistency between gene expression values is fed back to the gene set” is considered with the help of class-consistent technology, and fuzzy symmetric relations on the cell set of a scgd-space are induced. In addition, fuzzy rough approximations in a scgd-space are defined. Next, FRIC-model is given. This model employs the iterative computation strategy to define fuzzy rough approximations and dependency functions. A gene selection algorithm based on this model is designed. Finally, the designed algorithm is testified in several publicly open ge-data sets to estimate its performance. The experimental results show that the designed algorithm is more effective than some existing algorithms.

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Acknowledgements

The authors would like to thank the editors and the anonymous reviewers for their valuable comments and suggestions, which have helped immensely in improving the quality of the paper. This work is supported by Guangxi First-class Discipline Statistics Construction Project Fund, Natural Science Foundation of Guangxi Province (2021GXNSFAA220076, 2021GXNSFAA220114), Key Fields Project of Universities in Guangdong Province (2023ZDZX1063, 2023ZDZX1065, 2021ZDZX4109) and Scientific Research Platform of Guangdong Songshan Polytechnic (2022xjkypt02).

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Authors and Affiliations

  1. School of Computer and Information Engineering, Guangdong Songshan Polytechnic, Shaoguan, Guangdong, 512126, People’s Republic of China

    Jie Zhang & Yuxian Wang

  2. School of Big Data and Artificial Intelligence, Guangxi University of Finance and Economics, Nanning, Guangxi, 530003, People’s Republic of China

    Guangji Yu

  3. School of Computer Science and Engineering, Yulin Normal University, Yulin, Guangxi, 537000, People’s Republic of China

    Dan Huang

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  1. Jie Zhang
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Zhang, J., Yu, G., Huang, D. et al. Gene selection in a single cell gene decision space based on class-consistent technology and fuzzy rough iterative computation model. Appl Intell 53, 30113–30132 (2023). https://doi.org/10.1007/s10489-023-05115-0

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