From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline
Abstract | Introduction | Description of the biological experiment | Preliminary analysis | Downloading the read counts | Adding gene annotation | Design matrix | Filtering to remove low counts | Library size normalization | Exploring differences between libraries | Dispersion estimation | Differential expression analysis | Testing for differential expression | Differential expression above a fold-change threshold | Heat map clustering | Analysis of deviance | Complicated contrasts | Pathway analysis | Gene ontology analysis | KEGG pathway analysis | FRY gene set tests | Camera gene set enrichment analysis | Packages used | Read alignment and quantification | Download raw sequence files from the SRA | Accuracy of base-calling | Build a genome index | Aligning reads | Quantifying read counts for each gene | Data and software availability | Author contributions | Grant information | Acknowledgments | How to cite | References
Rendered fromedgeRQL.Rmdusingknitr::rmarkdown