Identification of SARS-CoV-2 origin: Using Ngrams, principal component analysis and Random Forest algorithm
Hamoucha El Boujnouni1, Mohamed Rahouti1, Mohamed El Boujnouni2
1Research Center of Plant and Microbial Biotechnologies, Biodiversity, and Environment, Faculty of Sciences, Mohammed V University in Rabat, PO Box 1014, Morocco.
Informatics in Medicine Unlocked
|April 26, 2021
Summary
This study investigated the origin of the SARS-CoV-2 virus. Findings reveal significant genomic similarities between SARS-CoV-2 and pangolin coronaviruses, suggesting pangolins as potential hosts.
Area of Science:
- Virology
- Genomics
- Computational Biology
Background:
- COVID-19, caused by SARS-CoV-2, is a rapidly spreading global pandemic.
- Understanding the virus's origin is crucial for developing effective treatments and prevention strategies.
Purpose of the Study:
- To determine the origin of the SARS-CoV-2 virus.
- To compare the nucleic acid sequence of SARS-CoV-2 with other coronaviridae family members.
Main Methods:
- Utilized a novel approach combining Ngrams, Principal Component Analysis (PCA), and Random Forest algorithm.
- Ngrams for text categorization, PCA for dimensionality reduction, and Random Forest for supervised classification.
- Analyzed SARS-CoV-2 genomes from global locations.
Main Results:
- Identified significant genomic similarities between SARS-CoV-2 and pangolin coronaviruses.
- Experimental results confirm previous findings suggesting pangolins as potential hosts.
- The study provides strong evidence for the role of pangolins in SARS-CoV-2 emergence.
Conclusions:
- Pangolins are strongly implicated as a potential host in the emergence of SARS-CoV-2.
- The applied computational methods offer a robust framework for viral origin studies.
- Further research into pangolin-borne coronaviruses is warranted.
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