N-of-one differential gene expression without control samples using a deep generative model

Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can identify the closest normal representation for a...

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Detalles Bibliográficos
Autores principales: Prada-Luengo, Iñigo, Schuster, Viktoria, Liang, Yuhu, Terkelsen, Thilde, Sora, Valentina, Krogh, Anders
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655485/
https://www.ncbi.nlm.nih.gov/pubmed/37974217
http://dx.doi.org/10.1186/s13059-023-03104-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655485/
https://www.ncbi.nlm.nih.gov/pubmed/37974217
http://dx.doi.org/10.1186/s13059-023-03104-7

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