Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS
Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suit...
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| Published in: | Nature protocols Vol. 18; no. 12; pp. 3690 - 3731 |
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| Main Authors: | , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
London
Nature Publishing Group UK
01.12.2023
Nature Publishing Group |
| Subjects: | |
| ISSN: | 1754-2189, 1750-2799, 1750-2799 |
| Online Access: | Get full text |
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