This document explains how to run the SARS-CoV-2 analysis workflow and where to find the final outputs.
Analyze SARS-CoV-2 genomic sequences for three US states:
- California
- New York
- Texas
Main workflow notebook:
- bio-finall.ipynb
Install Python dependencies:
pip install -r requirements.txtRecommended environment:
- Python 3.10+
- Jupyter Notebook or VS Code Notebook
- Open bio-finall.ipynb
- Run cells from top to bottom in order
- Do not skip preprocessing cells because downstream steps depend on generated files
- If a cell uses an absolute local path, replace it with your local project path
After successful execution, these folders and files are the key outputs.
-
CALIFORNIA/
- cleaned_California_data.csv
- sequences.fasta
- california_msa.fasta
- consensus_california.fasta
- tree_from_scratch.nwk
- California_mutation_hotspot.png
-
NEWYORK/
- cleaned_New_York_data.csv
- sequences.fasta
- newyork_msa.fasta
- consensus_newyork.fasta
- tree_from_scratch.nwk
- New York_mutation_hotspot.png
-
TEXAS/
- cleaned_Texas_data.csv
- sequences.fasta
- texas_msa.fasta
- consensus_texas.fasta
- tree_from_scratch.nwk
- Texas_mutation_hotspot.png
- consenses/
- consensus_california.fasta
- consensus_newyork.fasta
- consensus_texas.fasta
- final_consensus_tree.png
- phylogenetic_tree_cleaned.png
Use this checklist after running the notebook:
- All three cleaned CSV files exist in CALIFORNIA, NEWYORK, TEXAS
- All three consensus FASTA files exist in consenses
- At least one .nwk tree file exists per state folder
- final_consensus_tree.png and phylogenetic_tree_cleaned.png are generated
- The repository excludes unrelated contour/pipe image artifacts by design.
- One very large file was intentionally excluded from version control to satisfy GitHub limits.