A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data

BACKGROUND: Single-cell RNA sequencing (scRNAseq) data always involves various unwanted variables, which would be able to mask the true signal to identify cell-types. More efficient way of dealing with this issue is to extract low dimension information from high dimensional gene expression data to r...

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Detalles Bibliográficos
Autores principales: Sun, Shiquan, Chen, Yabo, Liu, Yang, Shang, Xuequn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449882/
https://www.ncbi.nlm.nih.gov/pubmed/30953530
http://dx.doi.org/10.1186/s12918-019-0699-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449882/
https://www.ncbi.nlm.nih.gov/pubmed/30953530
http://dx.doi.org/10.1186/s12918-019-0699-6

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