• Goal: customized and semi-automated analysis of microarray and bulk RNAseq data

• Authors: Laure Cougnaud, Kirsten Van Hoorde, Michela Pasetto, Katarzyna Górczak, Yingjie Zhang

• Tool: R package transcriptomicsTemplates and associated templates in RMarkdown format

The user copies the original template and modifies towards a personal RMarkdown master document containing analysis-specific input parameters.

Running the RMarkdown master document:

• calls other child templates contained in the package (do not need manual modifications)

• creates:

  • an html report file associated to the Rmd template
  • objects/graphs folders with results/visualizations

• unsupervised analysis (required)
• differential expression analysis (optional)
• overlap analysis (optional)
• pairwise comparison analysis (optional)

• ALL dataset
• microarrays from patients with acute lymphoblastic leukemia
• covariates of interest:
  • gender: male/female
  • different disease type: B-cell/T-cell
  • different disease stage: 1 to 4
  • remission achieved or refractory
    
• data from: Gene expression profile of adult T-cell acute lymphocytic leukemia identifies distinct subsets of patients with different response to therapy and survival, Chiaretti, et al. ,Blood type, 2004, 103

For a first glance at the data: spectral map of the entire dataset or a subset of samples of interest:

• with covariates-related aesthetics
• with different levels of annotation: sample, gene, gene set
• visualize genes/show table of pathways with highest score

• For microarray: limma

• For RNAseq: with edgeR and DESeq2

• several analyses of interest

• need to specify input model (design matrix, lmFit and eBayes)

• for each analysis, results are reported with:

  • volcano plots
  • top affected genes
  • top affected pathways

• with the MLP package
• Gene Ontology (GO) databases (with the possibility to add additional pathway databases if specified by the user)
• results reporting:
  • tables of top pathways
  • visualizations: barplot of pathway significance and GO graph

The transcriptomicsTemplates package is a transcriptional analysis workflow:

• facilitates the analysis of transcriptional data on a daily basis

• standardize reports

• time-saving and less error-prone