Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach
Abstract Gene expression data holds the potential to shed light on multiple biological processes at once. However, data analysis methods for single cell sequencing mostly focus on finding cell clusters or the principal progression line of the data. Data analysis for spatial transcriptomics mostly ad...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-75314-3 |
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