EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments
University of Wisconsin–Madison · Morgridge Institute for Research
Abstract
MOTIVATION: Messenger RNA expression is important in normal development and differentiation, as well as in manifestation of disease. RNA-seq experiments allow for the identification of differentially expressed (DE) genes and their corresponding isoforms on a genome-wide scale. However, statistical methods are required to ensure that accurate identifications are made. A number of methods exist for identifying DE genes, but far fewer are available for identifying DE isoforms. When isoform DE is of interest, investigators often apply gene-level (count-based) methods directly to estimates of isoform counts. Doing so is not recommended. In short, estimating isoform expression is relatively straightforward for some…
Citation impact
- FWCI
- 40.08
- Percentile
- 100%
- References
- 33
Authors
10- NLNing LengCorresponding
University of Wisconsin–Madison, Morgridge Institute for Research
- JAJohn A. Dawson
University of Wisconsin–Madison, Morgridge Institute for Research
- JAJames A. Thomson
University of Wisconsin–Madison, Morgridge Institute for Research
- VRVictor Ruotti
University of Wisconsin–Madison, Morgridge Institute for Research
- AIAnna I. Rissman
University of Wisconsin–Madison, Morgridge Institute for Research
Topics & keywords
- Bayes' theorem
- Inference
- Computer science
- Bayes factor
- Bayesian inference
- Artificial intelligence
- Bayesian probability
- Machine learning