Tumor-Normal Variant Analysis Pipeline using Nextflow

Project Overview

This project demonstrates a modular bioinformatics workflow for tumor-normal sequencing data analysis using Nextflow DSL2. The pipeline performs quality control, read trimming, sequence alignment, variant analysis preparation, and variant annotation. The project also includes IGV-based visualization for comparing tumor and normal samples.

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Objectives

• Perform quality assessment of raw sequencing reads
• Trim adapters and low-quality bases
• Align sequencing reads to the human reference genome (hg38)
• Generate sorted and indexed BAM files
• Perform variant analysis preparation
• Annotate variants using ANNOVAR
• Visualize genomic variants using IGV
• Compare tumor and normal samples at selected genomic loci

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Workflow Diagram

FASTQ
  ↓
FastQC
  ↓
Fastp
  ↓
BWA-MEM
  ↓
SAMtools
  ↓
GATK Variant Analysis
  ↓
ANNOVAR Annotation
  ↓
IGV Validation

Tools Used

Tool	Purpose
Nextflow DSL2	Workflow management
FastQC	Read quality assessment
Fastp	Read trimming and filtering
BWA-MEM	Sequence alignment
SAMtools	BAM processing and indexing
GATK	Variant analysis preparation
ANNOVAR	Variant annotation
IGV	Variant visualization

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Input Data

Input files:

tumor_R1.fastq.gz
tumor_R2.fastq.gz
normal_R1.fastq.gz
normal_R2.fastq.gz

Reference genome:

hg38.fa

The pipeline accepts paired-end FASTQ sequencing reads from tumor and normal samples.

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Running the Pipeline

Individual modules were developed and tested separately.

Example commands:

nextflow run fastqc.nf

nextflow run fastp.nf

nextflow run bwa_gatk.nf

nextflow run annovar.nf

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Output Files

The pipeline generates:

Quality Control

• FastQC HTML reports
• FastQC ZIP reports

Read Trimming

• Trimmed FASTQ files
• Fastp HTML report
• Fastp JSON report

Alignment

• Sorted BAM files
• BAM index (.bai) files

Variant Annotation

• Annotated VCF files
• Multianno text reports

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IGV Visualization

Integrated Genomics Viewer (IGV) was used to inspect aligned reads and validate genomic variants.

Example screenshots are available in:

examples/
├── igv_tumor.png
├── igv_normal.png

Observed features:

• Read alignment patterns
• Coverage differences
• Variant-supporting reads
• Tumor-normal comparison at selected loci

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Tumor vs Normal Comparison

A comparative visualization was performed using IGV.

Key observations:

• Variants present in tumor reads can be inspected visually.
• Read coverage between tumor and normal samples can be compared.
• Candidate somatic mutations may be identified through comparative analysis.

Detailed observations are available in:

examples/comparison.md

Future Improvements

• Complete end-to-end workflow integration through a single main.nf pipeline
• Add automated variant calling workflow
• Generate MultiQC summary reports
• Add containerized execution using Docker/Singularity
• Support large-scale cohort analysis
• Integrate CNV and structural variant analysis

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References

1. Nextflow Documentation
2. FastQC Documentation
3. Fastp Documentation
4. BWA Documentation
5. SAMtools Documentation
6. GATK Documentation
7. ANNOVAR Documentation
8. IGV Documentation

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Author

Md Mobarak Ansari

Bioinformatics and Genomics Enthusiast