Bioinformatics – Structural Variation Detection (Lact-FinderSV)

📌 Project Overview

This project focuses on the identification of structural variations in a bacterial genome through comparison with a reference genome. The analysis is performed using next-generation sequencing (NGS) data and a combination of bioinformatics tools and custom-developed scripts.

The reference genome is Lactobacillus casei, while the target genome (lact.sp) is a simulated organism containing artificial structural variations such as insertions, deletions, and inversions.

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🎯 Objectives

• Align sequencing reads to a reference genome

• Analyze coverage and mapping quality

• Detect structural variations (SVs), including:

  • Long and short insertions
  • Long and short deletions
  • Inversions

• Develop custom tracks for deeper genomic analysis

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🛠️ Tools & Technologies

• BWA – sequence alignment
• Samtools – SAM/BAM file processing
• IGV (Integrative Genomics Viewer) – visualization
• Python – custom track generation

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📂 Project Structure

• Code/ – Python scripts for track generation
• Img/ – images from analysis
• Plot IGV/ – IGV screenshots
• Wig/ – generated track files (.wig)

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📊 Analysis Performed

The project includes:

• Sequence coverage analysis
• Physical coverage analysis
• Single mate analysis
• Fragment length evaluation
• Orientation analysis
• Detection of anomalous mate pairs

Custom tracks were implemented to enhance the detection of structural variations and improve interpretability of genomic regions.

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🚀 How to Run

1. Index the reference genome:

   bwa index reference.fasta
   

2. Align reads:

   bwa mem reference.fasta reads1.fastq reads2.fastq > output.sam
   

3. Convert and sort:

   samtools view -bS output.sam > output.bam
   samtools sort output.bam -o sorted.bam
   samtools index sorted.bam
   

4. Generate custom tracks using provided Python scripts

5. Load .bam and .wig files into IGV for visualization

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⚠️ Academic Use Notice

This project was developed as part of a university assignment in Bioinformatics (LM-18 UniPD).

It is intended for educational purposes only. Unauthorized copying, reuse, or submission of this work (in whole or in part) as original work for academic evaluation is strictly prohibited.

If you use or reference this project, proper citation of the author is required.

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✍️ Author

Eleonora Signor

Master’s Degree in Computer Science University of Padua

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📅 Year

2021/2022