RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR
The University of Melbourne · Walter and Eliza Hall Institute of Medical Research · +3 more institutions
Abstract
The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the results obtained informing future experiments and validation studies. In this workflow article, we analyse RNA-sequencing data from the mouse mammary gland, demonstrating use of the popular edgeR package to import, organise, filter and normalise the data, followed by the limma package with its voom method, linear modelling and empirical Bayes moderation to assess differential expression and perform gene set testing.…
Citation impact
- FWCI
- 16.71
- Percentile
- 100%
- References
- 25
Authors
5- CWCharity W. LawCorresponding
The University of Melbourne, Walter and Eliza Hall Institute of Medical Research
- MAMonther Alhamdoosh
CSL (United Kingdom), CSL (Australia)
- SSShian Su
The University of Melbourne, Walter and Eliza Hall Institute of Medical Research, Peter MacCallum Cancer Centre
- GKGordon K. Smyth
The University of Melbourne, Walter and Eliza Hall Institute of Medical Research
- MEMatthew E. Ritchie
The University of Melbourne, Walter and Eliza Hall Institute of Medical Research
Topics & keywords
- Bioconductor
- Computer science
- Workflow
- Computational biology
- R package
- Data mining
- Pipeline (software)
- Biology