Publications by authors named "Cheng-Yang Ji"
Genomic evidence for divergent co-infections of co-circulating SARS-CoV-2 lineages.
Comput Struct Biotechnol J
July 2022
Article Synopsis
- Co-infection of RNA viruses, like SARS-CoV-2, can lead to more severe symptoms and poses challenges for tracking and identifying these infections in patients.
- A new method called Cov2Coinfect utilizes hypergeometric distribution to analyze a large dataset, allowing researchers to identify co-infected variants in over 50,000 deep sequencing samples.
- Findings show a co-infection rate of 0.3-0.5% in SARS-CoV-2 positive samples, with co-infected variants aligning with regional virus lineages, emphasizing the need for improved monitoring of co-infected patients for effective disease management.
Early identification of adaptive mutations could provide timely help for the control and prevention of the COVID-19 pandemic. The fast accumulation of SARS-CoV-2 sequencing data provides important support, while also raising a great challenge for the recognition of adaptive mutations. Here, we proposed a computational strategy to detect potentially adaptive mutations from their fixed and parallel patterns in the phylogenetic trajectory.
View Article and Find Full Text PDFSince the outbreak of SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, the viral genome has acquired numerous mutations with the potential to increase transmission. One year after its emergence, we now further analyze emergent SARS-CoV-2 genome sequences in an effort to understand the evolution of this virus.
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