RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR
Open Access
- 17 June 2016
- journal article
- Published by F1000 Research Ltd in F1000Research
- Vol. 5, 1408
- https://doi.org/10.12688/f1000research.9005.1
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- A pooled shRNA screen for regulators of primary mammary stem and progenitor cells identifies roles for Asap1 and Prox1BMC Cancer, 2015
- Orchestrating high-throughput genomic analysis with BioconductorNature Methods, 2015
- limma powers differential expression analyses for RNA-sequencing and microarray studiesNucleic Acids Research, 2015
- voom: precision weights unlock linear model analysis tools for RNA-seq read countsGenome Biology, 2014
- featureCounts: an efficient general purpose program for assigning sequence reads to genomic featuresBioinformatics, 2013
- The Subread aligner: fast, accurate and scalable read mapping by seed-and-voteNucleic Acids Research, 2013
- A scaling normalization method for differential expression analysis of RNA-seq dataGenome Biology, 2010
- edgeR: a Bioconductor package for differential expression analysis of digital gene expression dataBioinformatics, 2009
- Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRtNature Protocols, 2009
- BioMart and Bioconductor: a powerful link between biological databases and microarray data analysisBioinformatics, 2005