Trastuzumab DGE

This repository contains a differential gene expression (DGE) analysis for three distinct datasets of cardiomyocite expression after Trastuzumab treatment. The results of the different DGEs were then used for a meta-analysis.

The results from these analyses have now been published in OMICS and is available through the following DOI: https://doi.org/10.1089/omi.2024.0004

If you're reusing code or results from these analyses, please cite the paper as below:

What Powers Trastuzumab's Cardiotoxicity? Decoding Mitochondrial-Related Gene Expression Through Integrative Review and Meta-Analysis in Cardiomyocytes

Karoline dos Santos Rodrigues, Daniel Sturza Lucas Caetano, João Vitor Cavalcante, Rodrigo Dalmolin, Patrícia K. Ziegelmann, and Michael Andrades

OMICS: A Journal of Integrative Biology 2024 28:3, 103-110

Analysis Notebooks

• RNA-Seq - Source
• GSE107385 - Source
• Select Genes - Source
• Assemble Network - Source
• Overrepresentation analysis - Source

Repository Structure

.
├── analysis
├── data
├── renv
├── reports
└── results

• analysis
  • GSE107385.Rmd
    • DGE for the GSE107385 microarray dataset
  • RNASeq.Rmd
    • DGE for the other two RNA-Seq datasets
  • select_genes.Rmd
    • Select genes associated to mitophagy, autophagy and mitochondrial biogenesis
  • make_upset.R
    • Script to generate UpSet plot with intersections between grouped processes.
  • meta-analysis.R
    • Script to conduct the Meta-analysis to compare the treated (TRZ) and the control group.
    • Mean differences in the magnitude of gene expression changes (Log2 fold-change [Log2FC]) were estimated using random-effects models.
    • The analysis was conducted using the Metagen package.
  • assemble_network.Rmd
    • Assemble PPI network between metanalysis genes.
  • hypergeo.Rmd
    • Overrepresentation test for metanalysis genes and their intersections against the grouped processes.
• data
  • Plataformas.csv
    • Original metadata for the three studies
  • meta-analise.csv
    • Meta-analysis results
  • A directory for each dataset
    • Containing the count matrix for the microarray dataset and the Kallisto results for the RNA-Seq datasets
• reports
  • Analysis notebooks in HTML format
• results
  • All results from the analysis notebooks.