Unraveling the Hidden Dance: An Epistatic Exploration of 15 Million+ SARS-CoV-2 Genomes

This project provides a thorough analysis of the SARS-CoV-2 virus, emphasizing its lesser-known genetic makeup. The primary objective is to study the interactions of mutations in the non-Spike genes of SARS-CoV-2, known as epistasis. Through meticulous data analysis, we hope to decode patterns of simultaneous mutations and their combined effect on the virus's evolutionary trajectory.

Utilizing cutting-edge data analysis methodologies, our ambition is to uncover concealed interactions that could clarify the virus's properties, such as adaptability, transmission speed, and resistance against certain treatments. By harnessing machine learning, we aspire to craft models that predict the consequences these mutations might have on the virus, potentially informing upcoming evolution patterns.

A conclusive report and presentation will be crafted at the project's end, summarizing the crucial findings which could significantly aid our approach against future viral pandemics.

Tasks Overview

Outlined below are the distinct phases of the project:

1. Data Collection:

   • Source over 15 million SARS-CoV-2 genomes from GISAID and NCBI.
   • Endeavor for a comprehensive dataset.

2. Data Preprocessing:

   • Clean and preprocess data.
   • Spotlight on mutation detection in the non-Spike genes.

3. Mutation Analysis:

   • Discover patterns of coexisting mutations.
   • Offer initial signs of potential epistasis.

4. Interpretation of Epistasis:

   • Employ advanced analytical tools.
   • Uncover the nature of interactions between coexisting mutations – whether they're symbiotic or antagonistic.

5. Predictive Modeling using Machine Learning:

   • Leverage ML techniques to craft predictive models.
   • Predict potential mutation interaction implications on the virus's evolution.

6. Model Evaluation and Optimization:

   • Gauge model precision and make required refinements.
   • Strive for peak performance.

7. Data Representation:

   • Draft a comprehensive report.
   • Employ visual tools to communicate findings effectively.

8. Knowledge Dissemination:

   • Transform the report into a captivating presentation.
   • Elaborate on the research journey, its revelations, and its broader implications for future pandemic planning.

Contribute

To contribute to this project, fork the repository, make your changes and submit a pull request. For bugs, questions, and discussions, please use the Issues section.

License

This project is licensed under the MIT License.

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By being a part of this project, you are making a significant contribution to the fight against SARS-CoV-2 and potentially shaping the approach for future pandemics. Let's unravel the mysteries of this virus together.