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bioRxiv · 10.1101/2025.09.03.674100

DAESC+: High-performance, integrated software for single-cell allele-specific expression data

Cui, T.·Qi, G.
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Abstract

Single-cell allele-specific expression (ASE) provides valuable insights into gene regulatory mechanisms. However, its utility is limited by the lack of dedicated computational tools. We present DAESC+, an end-to-end software package for the processing and analysis of single-cell ASE. The preprocessing module, DAESC-P, is a user-friendly bioinformatics pipeline to obtain ASE counts from multiplexed scRNA-seq data. The analysis module, DAESC-GPU, is a scalable tool for differential ASE analysis powered by graphics processing units (GPUs). We demonstrated that DAESC-P is more accurate than the existing SALSA pipeline. DAESC-GPU is dozens of times faster than our previous method (DAESC) and scalable to over a million cells. Applying DAESC+ to a subset of the OneK1K cohort, we identified 15 genes exhibiting differential regulatory patterns between naive and central memory CD4+ T cells, and 2 genes between naive and memory B cells.

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Cui, T., Qi, G.. 2025-09-09. DAESC+: High-performance, integrated software for single-cell allele-specific expression data. https://doi.org/10.1101/2025.09.03.674100

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