Cargando…
An NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data
Single-cell RNA sequencing has enabled researchers to quantify the transcriptomes of individual cells, infer cell types and investigate differential expression among cell types, which will lead to a better understanding of the regulatory mechanisms of cell states. Transcript diversity caused by phen...
Autores principales: | Matsumoto, Hirotaka, Hayashi, Tetsutaro, Ozaki, Haruka, Tsuyuzaki, Koki, Umeda, Mana, Iida, Tsuyoshi, Nakamura, Masaya, Okano, Hideyuki, Nikaido, Itoshi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8499053/ https://www.ncbi.nlm.nih.gov/pubmed/34632380 http://dx.doi.org/10.1093/nargab/lqz020 |
Ejemplares similares
-
Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets
por: Ozaki, Haruka, et al.
Publicado: (2020) -
Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs
por: Hayashi, Tetsutaro, et al.
Publicado: (2018) -
Sctensor detects many-to-many cell–cell interactions from single cell RNA-sequencing data
por: Tsuyuzaki, Koki, et al.
Publicado: (2023) -
CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA sequencing
por: Sato, Kenta, et al.
Publicado: (2019) -
Benchmarking principal component analysis for large-scale single-cell RNA-sequencing
por: Tsuyuzaki, Koki, et al.
Publicado: (2020)