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bioRxiv · 10.64898/2026.10.01.755876

scStable: assessing scRNA-seq analysis stability under bulk-derived between-sample variation

Jiang, C.·Li, J. J.
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Abstract

Single-cell RNA sequencing (scRNA-seq) studies often profile only one or a few biological samples, limiting assessment of discovery stability under between-sample variation. We present scStable, a framework for assessing scRNA-seq analysis stability by generating synthetic samples that preserve cell-level heterogeneity from a single-sample reference while injecting bulk-derived between-sample variation. In gastric cancer data comprising 21 matched scRNA-seq and bulk RNA-seq profiles, scStable better recapitulates observed between-sample variation than ZINB-WaVE, subsampling, and Gaussian noise injection. Using synthetic sam-ples, scStable enables stability-aware analysis, including prioritization of stable differentially expressed genes and selection of clustering methods and hyperparameters.

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Jiang, C., Li, J. J.. 2026-10-08. scStable: assessing scRNA-seq analysis stability under bulk-derived between-sample variation. https://doi.org/10.64898/2026.10.01.755876

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