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The study aims to enhance marker gene discovery and clustering accuracy using an optimization framework called CORTADO.

April 17, 2026Bioinformatics Advances0 citationsOpen Access

CORTADO: Hill Climbing Optimization for Cell-Type Specific Marker Gene Discovery and Clustering Accuracy Improvement

MLMusaddiq K LodiVirginia Commonwealth University LCLeliani ClarkVirginia Commonwealth University SRSatyaki RoyUniversity of Alabama in Huntsville

Key Points

The study aims to enhance marker gene discovery and clustering accuracy using an optimization framework called CORTADO.
Developed the CORTADO framework utilizing hill-climbing optimization.
Maximized differential expression while minimizing redundancy and enforcing sparsity.
Evaluated performance against brain, immune, spatial, and cancer datasets to confirm efficacy.
Measured clustering accuracy using the Adjusted Rand Index (ARI) to compare against established methods.
CORTADO successfully identified biologically relevant markers in various datasets.
Significantly improved clustering accuracy, as indicated by higher ARI scores compared to state-of-the-art methods.
Showed a marked increase in interpretability and reduced redundancy in marker selection.

Abstract

Abstract The advent of single-cell RNA sequencing (scRNA-seq) has enhanced our ability to study cellular heterogeneity. Accurately identifying distinct subpopulations and their defining markers is critical for understanding tissue diversity. We introduce CORTADO, a hill-climbing optimization framework for marker discovery and clustering refinement. CORTADO maximizes differential expression, minimizes redundancy via cosine similarity, and enforces sparsity for interpretability. By using CORTADO-selected markers to inform the cell-type identification process, an iterative refinement approach markedly increases the Adjusted Rand Index (ARI), a metric that quantifies how well the clustering assignments align with gold-standard cell-type annotations. Benchmarking across brain, immune, spatial, and cancer datasets confirms that CORTADO delivers biologically relevant markers and consistently outperforms state-of-the-art methods in both marker discovery and clustering accuracy.

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