Cargando…
Benchmarking methods for detecting differential states between conditions from multi-subject single-cell RNA-seq data
Single-cell RNA-sequencing (scRNA-seq) enables researchers to quantify transcriptomes of thousands of cells simultaneously and study transcriptomic changes between cells. scRNA-seq datasets increasingly include multisubject, multicondition experiments to investigate cell-type-specific differential s...
Autores principales: | Junttila, Sini, Smolander, Johannes, Elo, Laura L |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487674/ https://www.ncbi.nlm.nih.gov/pubmed/35880426 http://dx.doi.org/10.1093/bib/bbac286 |
Ejemplares similares
-
Systematic benchmarking of statistical methods to assess differential expression of circular RNAs
por: Buratin, Alessia, et al.
Publicado: (2023) -
IBRAP: integrated benchmarking single-cell RNA-sequencing analytical pipeline
por: Knight, Connor H, et al.
Publicado: (2023) -
A Markov random field model-based approach for differentially expressed gene detection from single-cell RNA-seq data
por: Zhu, Biqing, et al.
Publicado: (2022) -
Quantum annealing-based clustering of single cell RNA-seq data
por: Kubacki, Michal, et al.
Publicado: (2023) -
Self-supervised deep clustering of single-cell RNA-seq data to hierarchically detect rare cell populations
por: Lei, Tianyuan, et al.
Publicado: (2023)