Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2

Kailing Li; Audrey K Y Wang; Sheng Liu; Shuyi Fang; Alex Z Lu; Jikui Shen; Lei Yang; Chang-Deng Hu; Kai Yang; Jun Wan

doi:10.3389/fmed.2022.813964

Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2

Front Med (Lausanne). 2022 Apr 11:9:813964. doi: 10.3389/fmed.2022.813964. eCollection 2022.

Authors

Kailing Li¹, Audrey K Y Wang², Sheng Liu^{3

4}, Shuyi Fang¹, Alex Z Lu², Jikui Shen⁵, Lei Yang⁶, Chang-Deng Hu^{7

8}, Kai Yang⁶, Jun Wan^{1

3

4

9}

Affiliations

¹ Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, IN, United States.
² Park Tudor School, Indianapolis, IN, United States.
³ Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States.
⁴ Collaborative Core for Cancer Bioinformatics (C3B) shared by Indiana University Simon Comprehensive Cancer Center and Purdue University Center for Cancer Research, West Lafayette, IN, United States.
⁵ The Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
⁶ Herman B Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, United States.
⁷ Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, United States.
⁸ Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN, United States.
⁹ The Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States.

Abstract

The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2 (GESS v2 https://shiny.ph.iu.edu/GESS_v2/) is an updated version of GESS, which has offered a handy query platform to analyze single-nucleotide variants (SNVs) on millions of high coverages and high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete genomes provided by the Global Initiative on Sharing Avian Influenza Data (GISAID). Including the tools in the first version, the GESS v2 is embedded with new functions, which allow users to search SNVs, given the viral nucleotide or amino acid sequence. The GESS v2 helps users to identify SNVs or SARS-CoV-2 lineages enriched in countries of user's interest and show the migration path of a selected lineage on a world map during specific time periods chosen by the users. In addition, the GESS v2 can recognize the dynamic variations of newly emerging SNVs in each month to help users monitor SNVs, which will potentially become dominant soon. More importantly, multiple sets of analyzed results about SNVs can be downloaded directly from the GESS v2 by which users can conduct their own independent research. With these significant updates, the GESS v2 will continue to serve as a public open platform for researchers to explore SARS-CoV-2 evolutionary patterns from the perspectives of the prevalence and impact of SNVs.

Keywords: COVID-19; SARS-CoV-2; SNV; database; enrichment; lineage; newly emerging.