Abstract
Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification, allows to analyze the presence of the most common microbial organisms, their antibiotic resistance, the severity of the infection and the set of the most probable geographical locations from which the studied strain could have originated. The online platform integrates a user friendly interface which allows easy visualization of the results. We envision this tool will not only have immediate implications for management of the ongoing COVID-19 pandemic, but will also improve our readiness to respond to other infectious outbreaks.
Highlights
Coronaviruses (CoVs) are a group of viruses that can infect the respiratory, gastrointestinal, hepatic and central nervous systems of humans, livestock, avians, bats, mice, and other wild animals [1,2]
This article introduces COVIDomic, a new integrative multi-omics online platform designed to facilitate the analysis of the large amount of health data collected from COVID-19 patients
The COVIDomic platform includes a user-friendly interface and provides a set of bioinformatics tools for the analysis of multi-modal metatranscriptomic data to determine the origin of the coronavirus strain and the expected severity of the disease
Summary
Coronaviruses (CoVs) are a group of viruses that can infect the respiratory, gastrointestinal, hepatic and central nervous systems of humans, livestock, avians, bats, mice, and other wild animals [1,2]. The few coronaviruses known to circulate in the human population caused mild respiratory infections and were regarded as relatively harmless respiratory pathogens [3]. The emergence of the severe acute respiratory syndrome coronavirus (SARSCoV) and the Middle East Respiratory Syndrome (MERS) coronavirus demonstrated that coronaviruses can cause severe and eventually fatal respiratory tract infections in humans [4]. SARS-CoV-2 is the seventh member of the CoVs family known to infect humans, which include 229E, NL63, OC43, HKU1, MERS-CoV and SARS-CoV. Three of these strains proved to be highly pathogenic (SARS-CoV, MERS-CoV, and SARS-CoV-2) and caused an endemic of severe CoV disease [6]
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