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Zero-Inflated gaussian mixed models for analyzing longitudinal microbiome data
MOTIVATION: The human microbiome is variable and dynamic in nature. Longitudinal studies could explain the mechanisms in maintaining the microbiome in health or causing dysbiosis in disease. However, it remains challenging to properly analyze the longitudinal microbiome data from either 16S rRNA or...
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| Veröffentlicht in: | PLoS One |
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| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7652264/ https://ncbi.nlm.nih.gov/pubmed/33166356 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0242073 |
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