Differential Gene Expression Pipelines

Genomics · DEG Analysis · 2025–2026

Differential Gene Expression Pipelines

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DEG analysis pipelines for two disease contexts: lung cancer and asthma.

Both pipelines follow a reproducible workflow from raw count data through to biological interpretation.

Lung Cancer Pipeline

  • Identified a set of significantly dysregulated genes associated with lung tumour biology.
  • Generated reproducible analytical pipelines for transcriptomic biomarker discovery.
  • Demonstrated the utility of publicly available genomic datasets for cancer research.
  • Significance: the identification of differentially expressed genes may contribute to future biomarker discovery efforts and improve understanding of molecular pathways involved in lung cancer development and progression.

Asthma Pipeline

  • Identified genes significantly altered following corticosteroid treatment.
  • Generated functional enrichment profiles highlighting biological processes affected by therapy.
  • Developed a fully reproducible transcriptomic workflow for asthma treatment response analysis.
  • Significance: understanding molecular signatures associated with treatment response may contribute to personalised [NEEDS YOUR INPUT — see note below].

Both pipelines are fully documented and reproducible in R.

Key tools: R · DESeq2 · limma · GEO

📂 View GitHub Repository →

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