RNA-seq workflow: gene-level exploratory analysis and differential expression
Introduction | Experimental data | Preparing quantification input to DESeq2 | Transcript quantification and tximport / tximeta | Quantifying with Salmon | Reading in data with tximeta | DESeq2 import functions | SummarizedExperiment | Branching point | The DESeqDataSet object, sample information and the design formula | Starting from SummarizedExperiment | Starting from count matrices | Exploratory analysis and visualization | Pre-filtering the dataset | The variance stabilizing transformation and the rlog | Sample distances | PCA plot | PCA plot using Generalized PCA | MDS plot | Differential expression analysis | Running the differential expression pipeline | Building the results table | Other comparisons | Multiple testing | Plotting results | Counts plot | MA-plot | Gene clustering | Independent filtering | Independent Hypothesis Weighting | Annotating and exporting results | Exporting results | Plotting fold changes in genomic space | Removing hidden batch effects | Using SVA with DESeq2 | Using RUV with DESeq2 | Time course experiments | Appendix | Updated details on quantification | Downloading FASTQ files | Building the salmon index | Quantifying abundance with salmon | Producing a RangedSummarizedExperiment with tximeta | Session information | References
Rendered fromrnaseqGene.Rmdusingknitr::rmarkdown