Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data
Clustering cells based on similarities in gene expression is the first step towards identifying cell types in scRNASeq data. Here the authors incorporate biological knowledge into the clustering step to facilitate the biological interpretability of clusters, and subsequent cell type identification.
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| Main Authors: | , , , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2021
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| Subjects: | |
| Online Access: | https://doaj.org/article/5d61bdf78def44fd9d00e5d1ec5fd2c2 |
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| Summary: | Clustering cells based on similarities in gene expression is the first step towards identifying cell types in scRNASeq data. Here the authors incorporate biological knowledge into the clustering step to facilitate the biological interpretability of clusters, and subsequent cell type identification. |
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