Dhyayepatel/sars-cov2-gwas-gambia

GWAS of SARS-CoV-2 variants in a Gambian cohort — MSc Health Data Science 2024 # GWAS of SARS-CoV-2 Variants in a Gambian Cohort > MSc Health Data Science Project — University of [Your University], 2024 > Investigating whether viral genetic variation (SNPs) in SARS-CoV-2 influences patient viral load (CT values) in The Gambia. --- ## Overview This project applies genome-wide association study (GWAS) methodology to **1,643 SARS-CoV-2 whole-genome sequences** from The Gambia, each matched with RT-PCR cycle threshold (Ct) values as a proxy for viral load. The goal was to identify viral SNPs significantly associated with differences in Ct across infected individuals — and to rigorously assess whether any such associations reflect genuine biology or population structure artefacts. **Key finding:** A single SNP at position 15,222 initially appeared significant, but lost significance entirely when the genetically divergent A.29 lineage was removed — a textbook demonstration of how population stratification can produce spurious associations in viral GWAS. --- ## Repository Structure ``` ├── 01_installation/ # Tool setup: PLINK2, Pangolin, IQ-TREE, Jvarkit, JBrowse ├── 02_pangolin_analysis/ # Lineage assignment and top 10 lineage extraction ├── 03_alignment/ # done through SEAVIEW GUI ├── 04_fasta_to_plink/ # VCF generation (Jvarkit), biallelic filtering, PLINK conversion ├── 05_ct_data_cleaning/ # CT count cleaning and PLINK phenotype formatting (R) ├── 06_gwas/ # QC, LD pruning, simple linear regression (PLINK2) + automated GWAS script ├── 07_phylogenetic_tree/ # Maximum likelihood tree construction (R: ape, phangorn, ggtree) ├── 08_pca/ # Population structure analysis (PLINK2 + R) ├── 09_three_model_gwas/ # Three-model framework for population structure control ├── 10_snp_annotation/ # SNP-to-gene mapping and amino acid analysis ├── Analysis_script_R # All Analysis including linear regressions and custom figures └── README.md ``` --- ## Methods …