ridmahoq/sars-cov2_genomic-analysis

A reference-based computational pipeline is used to identify mutation patterns and genome similarity among 1,001 complete SARS-CoV-2 genomes from Africa. # SARS-CoV-2 Genomic Variation and MST Analysis This project analyzes SARS-CoV-2 genome sequences using bioinformatics and data science techniques to identify SNPs, indels, mutation frequencies, and genomic relationships through Minimum Spanning Tree (MST) analysis. ## Methods - Multiple sequence alignment - SNP and indel detection - Mutation frequency analysis - Distance matrix computation - Minimum Spanning Tree construction - Statistical analysis - Network visualization using Cytoscape ## Tools and Libraries - Python - pandas - NumPy - Biopython - scikit-learn - matplotlib - seaborn - NetworkX - Cytoscape ## Project structure - plots/ contain visualization outputs - stats/ contain statistical output files - final_project.ipynb is the complete analysis notebook - hoq_final_project_report.pdf is the final project report - others are other output files ## Example Outputs ### MST Network ### Manhattan Plot