nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes

Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, a scalable approach to identify spatially variable genes based on nearest-neighbor Gaussian processes. Our...

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Detalles Bibliográficos
Autores principales: Weber, Lukas M., Saha, Arkajyoti, Datta, Abhirup, Hansen, Kasper D., Hicks, Stephanie C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333391/
https://www.ncbi.nlm.nih.gov/pubmed/37429865
http://dx.doi.org/10.1038/s41467-023-39748-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333391/
https://www.ncbi.nlm.nih.gov/pubmed/37429865
http://dx.doi.org/10.1038/s41467-023-39748-z

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