Cargando…
Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size
Motivation: RNA-seq experiments produce digital counts of reads that are affected by both biological and technical variation. To distinguish the systematic changes in expression between conditions from noise, the counts are frequently modeled by the Negative Binomial distribution. However, in experi...
Autores principales: | Yu, Danni, Huber, Wolfgang, Vitek, Olga |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3654711/ https://www.ncbi.nlm.nih.gov/pubmed/23589650 http://dx.doi.org/10.1093/bioinformatics/btt143 |
Ejemplares similares
-
Fast effect size shrinkage software for beta-binomial models of allelic imbalance
por: Zitovsky, Joshua P., et al.
Publicado: (2020) -
Sample Size under Inverse Negative Binomial Group Testing for Accuracy in Parameter Estimation
por: Montesinos-López, Osval Antonio, et al.
Publicado: (2012) -
Improved estimation in negative binomial regression
por: Kenne Pagui, Euloge Clovis, et al.
Publicado: (2022) -
Negative binomial additive model for RNA-Seq data analysis
por: Ren, Xu, et al.
Publicado: (2020) -
A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data
por: Wu, Hao, et al.
Publicado: (2013)