GitHub repository: Donmaston09/An-explainable-model-of-host-genetic-interactions-linked-to-Covid19-severity
Primary language: Jupyter Notebook
Created: 2021-11-12T01:58:34Z
Description: Prioritizing genetic variants and factors that are relevant to explaining patients’ severity susceptibility to the COVID-19 virus is important to generate hypotheses for disease/traits PheWAS association,  drug repurposing, identify individuals at unusually high or low risk, and contribute to global knowledge of the biology of SARS-CoV-2 infection and disease. Whole Exome Sequencing could provide insights about genetic factors modifying the interaction between the host (i.e. patients) and the virus. In this study, we expect to find a complex pattern of genetic factors interacting with the virus, if any at all. Most of the scholarly works done so far on mapping SARS-CoV-2 viral susceptibility among patients uses the Geno-Wide Association studies (GWS) in identifying chromosome loci and genetic variants related to the disease. However, an organic model explaining how these genetic factors concur in the establishment of susceptibility to severe infection when exposed to the SARS-CoV-2 coronavirus infection was not covered using the GWS approaches. Currently, there are limited usage of Machine learning (ML) techniques available to experts working with Whole-exome sequencing (WES) data sets related to COVID-19.