TY - JOUR
T1 - COVIDomic
T2 - A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity
AU - Naumov, Vladimir
AU - Putin, Evgeny
AU - Pushkov, Stefan
AU - Kozlova, Ekaterina
AU - Romantsov, Konstantin
AU - Kalashnikov, Alexander
AU - Galkin, Fedor
AU - Tihonova, Nina
AU - Shneyderman, Anastasia
AU - Galkin, Egor
AU - Zinkevich, Arsenii
AU - Cope, Stephanie M.
AU - Sethuraman, Ramanathan
AU - Oprea, Tudor I.
AU - Pearson, Alexander T.
AU - Tay, Savas
AU - Agrawal, Nishant
AU - Dubovenko, Alexey
AU - Vanhaelen, Quentin
AU - Ozerov, Ivan
AU - Aliper, Alex
AU - Izumchenko, Evgeny
AU - Zhavoronkov, Alex
PY - 2021
Y1 - 2021
N2 - Author summary 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. An analytical workflow includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification. These features allow studying the presence of common microbial organisms, their antibiotic resistance and the severity of the infection, as well as obtaining insights on the geographical locations from which the strain could have originated. Such openly distributed multi-modal platform will greatly accelerate the ongoing COVID-19 research and improve our readiness to respond to other infectious outbreaks.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.
AB - Author summary 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. An analytical workflow includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification. These features allow studying the presence of common microbial organisms, their antibiotic resistance and the severity of the infection, as well as obtaining insights on the geographical locations from which the strain could have originated. Such openly distributed multi-modal platform will greatly accelerate the ongoing COVID-19 research and improve our readiness to respond to other infectious outbreaks.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.
KW - RNA
KW - INFECTION
KW - BIOMARKER
KW - ALIGNMENT
KW - PROTEASE
KW - SARS
U2 - 10.1371/journal.pcbi.1009183
DO - 10.1371/journal.pcbi.1009183
M3 - Journal article
C2 - 34260589
SN - 1553-734X
VL - 17
JO - P L o S One
JF - P L o S One
IS - 7
M1 - e1009183
ER -