RETRACTED: Analysis of 329,942 SARS-CoV-2 records retrieved from GISAID database

Abstract

Background The SARS-CoV-2 virus caused a worldwide pandemic – although none of its predecessors from the coronavirus family ever achieved such a scale. The key to understanding the global success of SARS-CoV-2 is hidden in its genome. Materials and methods We retrieved data for 329,942 SARS-CoV-2 records uploaded to the GISAID database from the beginning of the pandemic until the January 8, 2021. A Python variant detection script was developed to process the data using pairwise2 from the BioPython library. Sequence alignments were performed for every gene separately (except ORF1ab, which was not studied). Genomes less than 26,000 nucleotides long were excluded from the research. Clustering was performed using HDBScan. Results Here, we addressed the genetic variability of SARS-CoV-2 using 329,942 samples. The analysis yielded 155 SNPs and deletions in more than 0.3% of the sequences. Clustering results suggested that a proportion of people (2.46%) was infected with a distinct subtype of the B.1.1.7 variant, which contained four to six additional mutations (G28881A, G28882A, G28883С, A23403G, A28095T, G25437T). Two clusters were formed by mutations in the samples uploaded predominantly by Denmark and Australia (1.48% and 2.51%, respectively). A correlation coefficient matrix detected 160 pairs of mutations (correlation coefficient greater than 0.7). We also addressed the completeness of the GISAID database, patient gender, and age. Finally, we found ORF6 and E to be the most conserved genes (96.15% and 94.66% of the sequences totally match the reference, respectively). Our results indicate multiple areas for further research in both SARS-CoV-2 studies and health science.

Genomic Surveillance of SARS-CoV-2 Variants in the Dominican Republic and Emergence of a Local Lineage

“…A total of 1149 SARS-CoV-2 whole-genome nucleotide sequences from the Dominican Republic were obtained from the Global Initiative on Sharing All Influenza Data (GISAID) database [ 22 , 23 , 24 ]. Of these, 940 sequences included the entire spike gene region and were selected to perform the analyses.…”

COVID-19 activity risk calculator as a gamified public health intervention tool

“…We implement here a simple COVID-19 Activity Risk Calculator (CovARC). We extract the number of confirmed cases by using the Johns Hopkins dataset 24 , 25 and cross-validate the number of confirmed cases using the Facebook surveys 26 dataset in order to obtain the upper and lower limits of the number of confirmed cases. We subtract confirmed cases from the preceding day’s number of confirmed cases in order to identify the number of active cases.…”

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India

“…This is one of the significant resources for analyzing SARS CoV-2 variants during pandemics, especially for VOC and VOI. Several scientists have used the GISAID to analyze the millions of sequences in different variants such as B.1.1.7 (Alpha; originated from the UK), B.1.617.2 (Delta; originated from India), P1 (Gamma; originated from Brazil), B.1.351 (Beta; originated from South Africa) ( Kalia et al, 2021 ; Zelenova et al, 2021 ; Khare et al, 2021 ). The classification methodology as proposed by Rambaut et al (2020) )was followed.…”