Cargando…
Stability of scRNA-Seq Analysis Workflows is Susceptible to Preprocessing and is Mitigated by Regularized or Supervised Approaches
BACKGROUND: Statistical methods developed to address various questions in single-cell datasets show increased variability to different parameter regimes. In order to delineate further the robustness of commonly utilized methods for single-cell RNA-Seq, we aimed to comprehensively review scRNA-Seq an...
Autores principales: | Durmaz, Arda, Scott, Jacob G |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9527995/ https://www.ncbi.nlm.nih.gov/pubmed/36199555 http://dx.doi.org/10.1177/11769343221123050 |
Ejemplares similares
-
scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
por: Zhang, Ziqi, et al.
Publicado: (2022) -
Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge
por: Mukherjee, Sumit, et al.
Publicado: (2018) -
Direct-seq: programmed gRNA scaffold for streamlined scRNA-seq in CRISPR screen
por: Song, Qingkai, et al.
Publicado: (2020) -
Preprocessing choices affect RNA velocity results for droplet scRNA-seq data
por: Soneson, Charlotte, et al.
Publicado: (2021) -
Contrastive self-supervised clustering of scRNA-seq data
por: Ciortan, Madalina, et al.
Publicado: (2021)