Systematic Guidelines for Effective Utilization of COVID-19 Databases in Genomic, Epidemiologic, and Clinical Research

Abstract

The pandemic has led to the production and accumulation of various types of data related to coronavirus disease 2019 (COVID-19). To understand the features and characteristics of COVID-19 data, we summarized representative databases and determined the data types, purpose, and utilization details of each database. In addition, we categorized COVID-19 associated databases into epidemiological data, genome and protein data, and drug and target data. We found that the data present in each of these databases have nine separate purposes (clade/variant/lineage, genome browser, protein structure, epidemiological data, visualization, data analysis tool, treatment, literature, and immunity) according to the types of data. Utilizing the databases we investigated, we created four queries as integrative analysis methods that aimed to answer important scientific questions related to COVID-19. Our queries can make effective use of multiple databases to produce valuable results that can reveal novel findings through comprehensive analysis. This allows clinical researchers, epidemiologists, and clinicians to have easy access to COVID-19 data without requiring expert knowledge in computing or data science. We expect that users will be able to reference our examples to construct their own integrative analysis methods, which will act as a basis for further scientific inquiry and data searching.

Choice of Target in the Genomes of Prototypic Strains to Recognize Subgenus of Coronaviruses

“…Широко известные мировому научному сообществу базы нуклеотидных данных такие, как GISAID (Global Initiative on Sharing Avian Influenza Data) [2], NCBI GenBank (National Center for Biotechnology Information GenBank) [3], ENA (European Nucleotide Archive) [4] и CNGBdb (China National GeneBank DataBase) [5], пополнились огромным числом секвенированных геномов коронавирусов, в частности, вызвавшем пандемию SARS-CoV-2 (Severe Acute Respiratory Syndromerelated сoronavirus 2) [6]. Были созданы новые веб-сервисы для обработки геномных данных [6,7] и изучены пути запросов системной информации в существующих базах данных по геномике, эпидемиологии и клиническим исследованиям SARS-CoV-2 [8]. Для обнаружения новых вирусов в общедоступных 5.7 миллионах экологически разнообразных баз данных, объемы нуклеотидных последовательностей в которых оцениваются как 10.2 × 10 15 нукл., разработана инфраструктура облачных вычислений Serratus [9].…”