Facilitate integrated analysis of single cell multiomic data by binarizing gene expression values
Abstract A cell type’s identity can be revealed by its transcriptome and epigenome profiles, both of which can be in flux temporally and spatially, leading to distinct cell states or subtypes. The popular and standard workflow for single cell RNA-seq (scRNA-seq) data analysis applies feature selecti...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-60899-8 |
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