Cargando…
Canonical correlation analysis for RNA-seq co-expression networks
Digital transcriptome analysis by next-generation sequencing discovers substantial mRNA variants. Variation in gene expression underlies many biological processes and holds a key to unravelling mechanism of common diseases. However, the current methods for construction of co-expression networks usin...
Autores principales: | Hong, Shengjun, Chen, Xiangning, Jin, Li, Xiong, Momiao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3632131/ https://www.ncbi.nlm.nih.gov/pubmed/23460206 http://dx.doi.org/10.1093/nar/gkt145 |
Ejemplares similares
-
Flexible expressed region analysis for RNA-seq with derfinder
por: Collado-Torres, Leonardo, et al.
Publicado: (2017) -
Network embedding-based representation learning for single cell RNA-seq data
por: Li, Xiangyu, et al.
Publicado: (2017) -
Linnorm: improved statistical analysis for single cell RNA-seq expression data
por: Yip, Shun H., et al.
Publicado: (2017) -
Gene expression variability and the analysis of large-scale RNA-seq studies with the MDSeq
por: Ran, Di, et al.
Publicado: (2017) -
Computational analysis of bacterial RNA-Seq data
por: McClure, Ryan, et al.
Publicado: (2013)