Biological process activity transformation of single cell gene expression for cross-species alignment
Single cell RNA-Seq data can report on cellular types and states, but low signal-to noise and sparse data can make interpretation of cellular state difficult. Here the authors propose a transformation strategy to map RNA-Seq data to biological process activities that are species-agnostic and allow f...
Guardado en:
Autores principales: | Hongxu Ding, Andrew Blair, Ying Yang, Joshua M. Stuart |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e32e60d474f14311b3573e25cb1cad5f |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics
por: Lucas Seninge, et al.
Publicado: (2021) -
Cross-species interference of gene expression
por: Irene de Bruijn, et al.
Publicado: (2018) -
Pairwise Biological Network Alignment Based on Discrete Bat Algorithm
por: Jing Chen, et al.
Publicado: (2021) -
Cross-species gene modules emerge from a systems biology approach to osteoarthritis
por: Alan James Mueller, et al.
Publicado: (2017) -
Single-cell analysis identifies dynamic gene expression networks that govern B cell development and transformation
por: Robin D. Lee, et al.
Publicado: (2021)