Cargando…
Linnorm: improved statistical analysis for single cell RNA-seq expression data
Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Usi...
Autores principales: | Yip, Shun H., Wang, Panwen, Kocher, Jean-Pierre A., Sham, Pak Chung, Wang, Junwen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5727406/ https://www.ncbi.nlm.nih.gov/pubmed/28981748 http://dx.doi.org/10.1093/nar/gkx828 |
Ejemplares similares
-
Linnorm: improved statistical analysis for single cell RNA-seq expression data
por: Yip, Shun H., et al.
Publicado: (2017) -
SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples
por: Yalamanchili, Hari Krishna, et al.
Publicado: (2014) -
LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data
por: Wan, Changlin, et al.
Publicado: (2019) -
RUV-III-NB: normalization of single cell RNA-seq data
por: Salim, Agus, et al.
Publicado: (2022) -
Statistical analysis of genetic interactions in Tn-Seq data
por: DeJesus, Michael A., et al.
Publicado: (2017)