ArticleSTAR protocols2026
Protocol for automated optimization of feature selection and clustering parameters in single-cell RNA-seq using scAutoTune.
Article in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Single-cell RNA sequencing (RNA-seq) analysis requires dataset-specific tuning of feature selection and clustering parameters. Here, we present a protocol for automated optimization of feature selection and clustering parameters in single-cell RNA-seq using scAutoTune. We describe steps for installing scAutoTune, preparing Seurat objects from public single-cell RNA-seq datasets, and performing grid-based parameter sweeping with optional Harmony batch correction. We then detail procedures for computing silhouette-based performance metrics, visualizing generalized additive model (GAM)-smoothed landscapes, and applying optimal settings to generate uniform manifold approximation and projection (UMAP) embeddings and interpretable clusters. For complete details on the use and execution of this protocol, please refer to Sun et al.
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