ena-STUDY-Clinical Bioinformatics Area-23-03-2021-18:21:14:172-129
Test datasets for impuSARS, a tool for the imputation of SARS-CoV-2 whole genome sequences from incomplete or partial sequences.
The current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences. However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium. An imputation method, impuSARS, has been developed to predict missing positions from the available sequencing data. Some of the test data described in the main paper are available in this ENA study.
The current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences. However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium. An imputation method, impuSARS, has been developed to predict missing positions from the available sequencing data. Some of the test data described in the main paper are available in this ENA study.