nf-final-cancer-rnaseq

RNA-seq differential expression in cancer — chromosome 17 (BRCA1 / TP53) 90-minute Nextflow introduction webinar.

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The biological story

Six cancer patients across three subtypes, each with tumor and matched normal tissue.

Patients	Subtype	Key finding
patient1, patient2	Breast (BRCA)	BRCA1 downregulated in tumor
patient3, patient4	Lung	TP53 downregulated in tumor
patient5, patient6	Colorectal	Both genes affected

The pipeline

data/samplesheet.csv  (12 samples: 6 patients × tumor + normal)
        │
        ▼
  [ Fastp ]      trim adapters, quality filter     → cleaned FASTQ
        │
        ▼
  [ Salmon ]     quantify transcript expression    → quant.sf per sample
        │
        ▼
  [ DESeq2 ]     differential expression           → results TSV + plots
  (PyDESeq2)     tumor vs normal, per patient (×6)
        │
        ▼
  [ MultiQC ]    aggregate QC                      → HTML report

Quick start

GitHub Codespaces (recommended)

1. Click Code → Codespaces → Create codespace on main
2. Wait for setup to complete — watch the terminal for the ✓ confirmation
3. If the terminal shows an error or closes before printing ✓, run manually:

   bash setup.sh

4. Test the pipeline:

   nextflow run pipeline/main.nf -profile docker,test -stub

See GETTING_STARTED.md for full details and troubleshooting.

Repository layout

.
├── pipeline/                   Nextflow pipeline
│   ├── main.nf
│   ├── modules/local/          fastp / salmon / deseq2 / multiqc
│   ├── subworkflows/local/     quantify / diff_expr
│   └── bin/run_deseq2.py       PyDESeq2 script
│
├── course/                     Teaching material (work through in order)
│   ├── 01_channels.nf
│   ├── 02_operators.nf
│   ├── 03_samplesheet.nf
│   ├── 04_first_module.nf
│   ├── 05_workflow.nf
│   ├── 06_containers.nf
│   ├── 07_config.nf
│   ├── 08_exercise.nf          Student exercise
│   ├── 08_exercise_solution.nf
│   └── REFERENCE.md            Quick-reference card
│
├── data/                       Synthetic FASTQs + samplesheet
├── reference/                  Salmon index (generated by setup.sh)
├── results/                    Pre-computed results (instructor use)
├── scripts/                    generate_reads.py
├── setup.sh                    Codespace initialization
├── nextflow.config             All profiles and parameters
└── .devcontainer/              Codespace configuration

Running course files

# No Docker required — instant
nextflow run course/01_channels.nf
nextflow run course/02_operators.nf
nextflow run course/03_samplesheet.nf

# Structure check — no images pulled, no data processed
nextflow run course/04_first_module.nf  -profile docker,test -stub
nextflow run course/05_workflow.nf      -profile docker,test -stub
nextflow run course/06_containers.nf    -profile docker,test -stub
nextflow run course/07_config.nf        -profile docker,test -stub
nextflow run course/08_exercise.nf      -profile docker,test -stub

# Real run — pulls containers and processes data (~2–5 min each)
nextflow run course/04_first_module.nf  -profile docker,test
nextflow run course/05_workflow.nf      -profile docker,test
nextflow run course/06_containers.nf    -profile docker,test
nextflow run course/07_config.nf        -profile docker,test
nextflow run course/08_exercise_solution.nf -profile docker,test

References

Tool	Citation
Nextflow	Di Tommaso et al., Nat. Biotechnol. 2017
Fastp	Chen et al., Bioinformatics 2018
Salmon	Patro et al., Nature Methods 2017
PyDESeq2	Muzellec et al., Bioinformatics 2023
DESeq2 model	Love et al., Genome Biology 2014
MultiQC	Ewels et al., Bioinformatics 2016

Image Source: nf-core/rnaseq RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.

License

MIT