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Dataset Information

Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes.


ABSTRACT: SARS-CoV-2 genomic sequencing efforts have scaled dramatically to address the current global pandemic and aid public health. However, autonomous genome annotation of SARS-CoV-2 genes, proteins, and domains is not readily accomplished by existing methods and results in missing or incorrect sequences. To overcome this limitation, we developed a novel semi-supervised pipeline for automated gene, protein, and functional domain annotation of SARS-CoV-2 genomes that differentiates itself by not relying on the use of a single reference genome and by overcoming atypical genomic traits that challenge traditional bioinformatic methods. We analyzed an initial corpus of 66,000 SARS-CoV-2 genome sequences collected from labs across the world using our method and identified the comprehensive set of know

SUBMITTER: Beck KL 

PROVIDER: S-EPMC8706859 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature