edgeR : a Bioconductor package for differential expression analysis of digital gene expression data
Garvan Institute of Medical Research · Walter and Eliza Hall Institute of Medical Research
Abstract
SUMMARY: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the…
Citation impact
- FWCI
- 46.13
- Percentile
- 100%
- References
- 11
Authors
3- MDMark D. RobinsonCorresponding
Garvan Institute of Medical Research, Walter and Eliza Hall Institute of Medical Research
- DJDavis J. McCarthy
Garvan Institute of Medical Research, Walter and Eliza Hall Institute of Medical Research
- GKGordon K. Smyth
Garvan Institute of Medical Research, Walter and Eliza Hall Institute of Medical Research
Topics & keywords
- Bioconductor
- Count data
- Computer science
- R package
- Computational biology
- Software
- Inference
- Biology