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Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks

Single-cell RNA sequencing technology promotes the profiling of single-cell transcriptomes at an unprecedented throughput and resolution. However, in scRNA-seq studies, only a low amount of sequenced mRNA in each cell leads to missing detection for a portion of mRNA molecules, i.e. the dropout probl...

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Detalles Bibliográficos
Autores principales:	Rao, Jiahua, Zhou, Xiang, Lu, Yutong, Zhao, Huiying, Yang, Yuedong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091052/ https://www.ncbi.nlm.nih.gov/pubmed/33997678 http://dx.doi.org/10.1016/j.isci.2021.102393

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