Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

Spatial transcriptomics technologies generate gene expression profiles with spatial context, requiring spatially informed analysis tools for three key tasks, spatial clustering, multisample integration, and cell-type deconvolution. We present GraphST, a graph self-supervised contrastive learning met...

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Detalles Bibliográficos
Autores principales: Long, Yahui, Ang, Kok Siong, Li, Mengwei, Chong, Kian Long Kelvin, Sethi, Raman, Zhong, Chengwei, Xu, Hang, Ong, Zhiwei, Sachaphibulkij, Karishma, Chen, Ao, Zeng, Li, Fu, Huazhu, Wu, Min, Lim, Lina Hsiu Kim, Liu, Longqi, Chen, Jinmiao
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/PMC9977836/
https://www.ncbi.nlm.nih.gov/pubmed/36859400
http://dx.doi.org/10.1038/s41467-023-36796-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977836/
https://www.ncbi.nlm.nih.gov/pubmed/36859400
http://dx.doi.org/10.1038/s41467-023-36796-3

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