RNA-Seq - Differential Exon Usage Analysis

2 minute read

RNA-Seq Workflow

  1. Read quality assessment, filtering and trimming
  2. Map reads against reference genome
  3. Perform read counting for required ranges (e.g. exonic gene ranges)
  4. Normalization of read counts
  5. Identification of differentially expressed genes (DEGs)
  6. Clustering of gene expression profiles
  7. Gene set enrichment analysis

Challenge Projects

Differential exon usage analysis with DEXseq

  • Run workflow from start to finish (steps 1-7) on RNA-Seq data set from Howard et al. (2013)
  • Challenge project tasks
    • Perform differential exon analysis with DEXseq. Assess the results as follows:
      • Identify genes that show differential exon usage according to DEXseq. Optionally, perform functional gene set enrichment analysis on the obained gene set.
      • Compare the results with the findings of the splice variant analysis reported by Howard et al (2013).


  • Anders S, Reyes A, Huber W (2012) Detecting differential usage of exons from RNA-seq data. Genome Res 22: 2008–2017 PubMed
  • Howard, B.E. et al., 2013. High-throughput RNA sequencing of pseudomonas-infected Arabidopsis reveals hidden transcriptome complexity and novel splice variants. PloS one, 8(10), p.e74183. PubMed
  • Guo Y, Li C-I, Ye F, Shyr Y (2013) Evaluation of read count based RNAseq analysis methods. BMC Genomics 14 Suppl 8: S2 PubMed
  • Hardcastle TJ, Kelly KA (2010) baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 11: 422 PubMed
  • Liu R, Holik AZ, Su S, Jansz N, Chen K, Leong HS, Blewitt ME, Asselin-Labat M-L, Smyth GK, Ritchie ME (2015) Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Nucleic Acids Res. doi: 10.1093/nar/gkv412. PubMed
  • Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15: 550 PubMed
  • Zhou X, Lindsay H, Robinson MD (2014) Robustly detecting differential expression in RNA sequencing data using observation weights. Nucleic Acids Res 42: e91 PubMed
Last modified 2022-05-25: some edits (2a1d3f13a)