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Reference Vector-guided Evolutionary Algorithm for cluster analysis of single-cell transcriptomes
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DOI：10.1016/j.cmpb.2025.108873.png)
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Abstract
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• A novel multi-objective algorithm for cluster analysis of single-cell transcriptomes. • Three new problem-aware mutation operators to improve each objective of the problem. • Evaluation with ten real scRNA-seq datasets and metrics widely used in the field. • Statistically significant improvements regarding the state-of-the-art methods. • Biological analysis of the solutions denoting a high agreement with the real clusters.
Keywords:
Multi-objective optimization
Reference Vector-guided Evolutionary Algorithm
Cluster analysis
Single-cell transcriptome
ScRNA-seq
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