Cargando…
Nonparametric expression analysis using inferential replicate counts
A primary challenge in the analysis of RNA-seq data is to identify differentially expressed genes or transcripts while controlling for technical biases. Ideally, a statistical testing procedure should incorporate the inherent uncertainty of the abundance estimates arising from the quantification ste...
Autores principales: | Zhu, Anqi, Srivastava, Avi, Ibrahim, Joseph G, Patro, Rob, Love, Michael I |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765120/ https://www.ncbi.nlm.nih.gov/pubmed/31372651 http://dx.doi.org/10.1093/nar/gkz622 |
Ejemplares similares
-
TreeTerminus —creating transcript trees using inferential replicate counts
por: Singh, Noor Pratap, et al.
Publicado: (2023) -
Inferential modeling of 3D chromatin structure
por: Wang, Siyu, et al.
Publicado: (2015) -
Accurate expression quantification from nanopore direct RNA sequencing with NanoCount
por: Gleeson, Josie, et al.
Publicado: (2021) -
Flexible expressed region analysis for RNA-seq with derfinder
por: Collado-Torres, Leonardo, et al.
Publicado: (2017) -
Alevin efficiently estimates accurate gene abundances from dscRNA-seq data
por: Srivastava, Avi, et al.
Publicado: (2019)