ArticleCommunications biology2025
A realistic FastQ-based framework FastQDesign for ScRNA-seq study design issues.
Article in Communications biology, 2025. 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 (scRNA-seq) has emerged as a powerful technology for characterizing transcriptomic profiles at single-cell resolution. It is crucial to consider both the number of cells and sequencing depth during library preparation. The existing methods are primarily simulation-based, rely on Unique Molecular Identifier (UMI) matrix, and have little context in the actual FastQ reads. Here we propose the first FastQ-based study design framework, named "FastQDesign," which leverages raw FastQ files from publicly available datasets as references and suggests an optimal design within a fixed budget. We demonstrate our framework through a synthetic dataset and applications to nine real-world datasets. Our study underscores the importance of an appropriate design to investigate the biology of heterogeneous cell populations and offers practical guidance considering cost-benefit trade-offs. A high-efficiency software suite is available at https://github.com/yuw444/FastQDesign .
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