This repo contains the codes used for P11636 project.

RNA-seq Pipeline

This RNA-seq analysis is performed using CQSperl via the performRNASeq_gencode_mm10 function.

The main pipeline configuration file is:
20240801_11636_RNAseq_mouse.rnaseq.pl

Executing this file generates analysis scripts, which can then be submitted to the SLURM system. All step-specific scripts are collected in the pipeline_codes folder.

Pipeline Workflow

The pipeline consists of the following steps:

1. Paired-end validation – Verifies paired-end sequencing data for each sample.
2. FastQC (raw) – Quality control of raw FASTQ files.
3. Cutadapt – Trims adapter sequences from reads.
4. Cutadapt validation – Ensures trimming success.
5. FastQC (post-trimming) – Quality control after adapter trimming.
6. FastQC summary – Generates a QC report for all samples.
7. STAR + featureCounts – Maps reads to the reference genome and quantifies gene expression.
8. Gene table generation – Creates the gene count table.
9. DESeq2 – Performs differential expression analysis.
10. WebGestalt ORA – Over-representation pathway enrichment analysis.
11. GSEA – Gene set enrichment analysis (GSEA) using all genes from DESeq2 results.
12. Final report – Compiles results into a summary report.

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Additional Enrichment Analysis

Beyond the default ORA and GSEA pathway enrichment analyses, we implemented additional enhancements. The corresponding code and dependency files are stored in the enrichment_plots folder.

1. Expanded Gene Sets

Additional gene sets for pathway enrichment analysis are available in enrichment_plots/geneset/:

• Custom gene sets:

  • Actin_Cell_Mobility
  • EMT
  • PI3K
  • Integrin
  • Wnt_signaling
  • P53_signaling
  • Innate_immune_response

• Publicly available gene sets:

  • Hallmark Genes (MSigDB)
  • Curated Gene Sets (MSigDB)
  • Regulatory Target Gene Sets (MSigDB)
  • Ontology Gene Sets (MSigDB)
  • Cell Type Signature Gene Sets (MSigDB)
  • GO_BP, GO_CC, GO_MF (WebGestaltR)
  • KEGG (WebGestaltR)
  • Reactome (WebGestaltR)
  • WikiPathways (WebGestaltR)

2. Figure Style Enhancements

Figures have been optimized for clarity and presentation.

3. Pathway Visualization (Pathview)

Pathway-specific visualizations are generated for:

• mmu04310 – Wnt signaling pathway
• mmu04810 – Regulation of actin cytoskeleton
• mmu04151 – PI3K-Akt signaling pathway
• mmu04115 – p53 signaling pathway

Running the Enrichment Analysis

1. Run run_webgestaltr_and_GSEA.r to generate ORA and GSEA results.
2. Render enrichment_plots/heather_report.rmd to generate an HTML report.