Cargando…
AntiSplodge: a neural-network-based RNA-profile deconvolution pipeline designed for spatial transcriptomics
With the current surge of spatial transcriptomics (ST) studies, researchers are exploring the deep interactive cell-play directly in tissues, in situ. However, with the current technologies, measurements consist of mRNA transcript profiles of mixed origin. Recently, applications have been proposed t...
Autores principales: | Lund, Jesper B, Lindberg, Eric L, Maatz, Henrike, Pottbaecker, Fabian, Hübner, Norbert, Lippert, Christoph |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549785/ https://www.ncbi.nlm.nih.gov/pubmed/36225530 http://dx.doi.org/10.1093/nargab/lqac073 |
Ejemplares similares
-
SpatialDWLS: accurate deconvolution of spatial transcriptomic data
por: Dong, Rui, et al.
Publicado: (2021) -
SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes
por: Elosua-Bayes, Marc, et al.
Publicado: (2021) -
Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data
por: Geras, Agnieszka, et al.
Publicado: (2023) -
DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence
por: Song, Qianqian, et al.
Publicado: (2021) -
Benchmarking of cell type deconvolution pipelines for transcriptomics data
por: Avila Cobos, Francisco, et al.
Publicado: (2020)