MaLiAmPi enables generalizable and taxonomy-independent microbiome features from technically diverse 16S-based microbiome studies

For studies using microbiome data, the ability to robustly combine data from technically and biologically distinct microbiome studies is a crucial means of supporting more robust and clinically relevant inferences. Formidable technical challenges arise when attempting to combine data from technicall...

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Detalles Bibliográficos
Autores principales: Minot, Samuel S., Garb, Bailey, Roldan, Alennie, Tang, Alice S., Oskotsky, Tomiko T., Rosenthal, Christopher, Hoffman, Noah G., Sirota, Marina, Golob, Jonathan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694490/
https://www.ncbi.nlm.nih.gov/pubmed/37939711
http://dx.doi.org/10.1016/j.crmeth.2023.100639

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694490/
https://www.ncbi.nlm.nih.gov/pubmed/37939711
http://dx.doi.org/10.1016/j.crmeth.2023.100639

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