Cargando…
Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference
Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the hig...
Autores principales: | Campbell, Kieran R., Yau, Christopher |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5117567/ https://www.ncbi.nlm.nih.gov/pubmed/27870852 http://dx.doi.org/10.1371/journal.pcbi.1005212 |
Ejemplares similares
-
Correction: Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference
Publicado: (2017) -
A descriptive marker gene approach to single-cell pseudotime inference
por: Campbell, Kieran R, et al.
Publicado: (2019) -
LVPT: Lazy Velocity Pseudotime Inference Method
por: Mao, Shuainan, et al.
Publicado: (2023) -
PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
por: Song, Dongyuan, et al.
Publicado: (2021) -
A robust and accurate single-cell data trajectory inference method using ensemble pseudotime
por: Zhang, Yifan, et al.
Publicado: (2023)