BRB-seq Pipeline

This repository contains scripts and resources for processing BRB-seq (Bulk RNA Barcoding and Sequencing) data to perform:

• Alignment and count matrix generation
• Differential gene expression (DGE) analysis using DESeq2
• Gene Set Enrichment Analysis (GSEA) using MSigDB hallmark and curated gene sets
• Visualization including PCA plots, volcano plots, and dotplots

Directory Structure

BRB_SEQ/
├── data/
│   ├── fastq/                 # Raw FASTQ files (R1, R2 for each lane)
│   ├── barcodes_96_V5A.tsv    # whitelist 
│   ├── sample_metadata.tsv    # metadata
│   └── wells_samples.tsv      # plate layout
├── logs/                      # STARsolo and pipeline logs
│   ├── brbseq_pipeline.err
│   ├── brbseq_pipeline.out
│   └── star_solo.log
├── results/
│   ├── matrix/                # Output count matrix (UMI counts)
│   ├── deseq2/                # Differential expression result tables
│   ├── volcano_plots/         # Volcano plots from DE results
│   ├── gsea/                  # GSEA results + plots
│   ├── pca/                   # PCA plots
│   ├── qc/                    # (optional) QC stats or reports
│   └── validation/            # Additional summary plots (PCA, etc.)
├── scripts/                   # All main scripts in order of execution
│   ├── 00_brb_seq_pipeline.sh         # Alignment & quantification using STARsolo
│   ├── 01_run_deseq2.r                # DESeq2-based differential analysis
│   ├── 02_make_volcano_plots.r        # Volcano plots of DEGs
│   ├── 03_gsea.r                      # GSEA with MSigDB (Hallmark, C2, C7)
│   ├── 04_gsea_plots.r               # Dotplot + heatmap of GSEA output
│   ├── generate_sample_metadata.py   # Parses plate layout into metadata
│   └── run_pipeline_job.sh           # Job submission wrapper for SCC
├── workdir/
│   ├── aligned/              # STARsolo output
│   └── merged/               # Merged fastqs
├── env.yml                   # Conda environment definition
├── env.sh                    # Environment/module loading
└── .gitignore

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Workflow

0. Run alignment & quantification
   Submit job via:

   qsub scripts/run_pipeline_job.sh
   

1. Run DESeq2 analysis

   Rscript scripts/01_run_deseq2.r
   

2. Create volcano plots

   Rscript scripts/02_make_volcano_plots.r
   

3. Run GSEA

   Rscript scripts/03_gsea.r
   

4. Plot GSEA dotplots

   Rscript scripts/04_gsea_plots.r
   

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Conda Environment

Install the pipeline dependencies via:

conda env create -f env.yml
conda activate brb_seq

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Author

Mohamed Yousry ElSadec

PhD Student in Bioinformatics, Boston University

Juan Fuxman Bass Lab

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License

MIT License