Detection of allele-specific expression in spatial transcriptomics with spASE
Author(s)
Zou, Luli S.; Cable, Dylan M.; Barrera-Lopez, Irving A.; Zhao, Tongtong; Murray, Evan; Aryee, Martin J.; Chen, Fei; Irizarry, Rafael A.; ... Show more Show less
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Spatial transcriptomics technologies permit the study of the spatial distribution of RNA at near-single-cell resolution genome-wide. However, the feasibility of studying spatial allele-specific expression (ASE) from these data remains uncharacterized. Here, we introduce spASE, a computational framework for detecting and estimating spatial ASE. To tackle the challenges presented by cell type mixtures and a low signal to noise ratio, we implement a hierarchical model involving additive mixtures of spatial smoothing splines. We apply our method to allele-resolved Visium and Slide-seq from the mouse cerebellum and hippocampus and report new insight into the landscape of spatial and cell type-specific ASE therein.
Date issued
2024-07-08Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Springer Science and Business Media LLC
Citation
Zou, L.S., Cable, D.M., Barrera-Lopez, I.A. et al. Detection of allele-specific expression in spatial transcriptomics with spASE. Genome Biol 25, 180 (2024).
Version: Final published version
ISSN
1474-760X