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Machine learning differentiates between bulk and pseudo-bulk RNA-seq datasets

Low, B. H.; Rashid, M. M.; Selvarajoo, K.

2025-07-01 bioinformatics
10.1101/2025.06.27.661895 bioRxiv
Show abstract

Modern synthetic data generators and deconvolution methods rely heavily on single-cell (sc) RNA- seq data. Aggregated scRNA-seq (pseudo-bulk) is commonly assumed to closely match true bulk RNA-seq, making it a dependable benchmark for developing and evaluating new bioinformatics methods. Here, we investigated paired bulk and scRNA-seq datasets using machine learning techniques to assess the fidelity of pseudo-bulk profiles. Our results demonstrate that pseudo-bulks differ substantially from bulk RNA-seq in both analytic metrics and biological processes.

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