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Spatial dissimilarity analysis in single-cell transcriptomics
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DOI：10.1016/j.crmeth.2025.101141.png)
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Abstract
En 中文
• We develop a statistical framework to analyze linked feature pairs in single-cell data • We use this method to detect and visualize alternative splicing events in neurons • We also demonstrate application to allele-specific gene expression in tumors • We provide software tools (PISA/Yano) to implement the method
Keywords:
single-cell genomics
single-cell RNA-seq
spatial transcriptomics
alternative splicing
allele-specific gene expression
cancer genomics
lineage trajectory
somatic mosaicism
CP: computational biology
CP: systems biology
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