CovidOutcome2: a tool for SARS-CoV2 mutation identification and for disease severity prediction
CovidOutcome2: a tool for SARS-CoV2 mutation identification and for disease severity prediction
Our goal was to develop a platform, CovidOutcome2, capable of predicting disease severity from viral mutation profiles using automated machine learning (autoML) and deep neural networks applied to the available large corpus of sequenced SARS-CoV2 genomes. CovidOutcome2 accepts either user-submitted genomes or user defined mutation combinations as the input. The output is a predicted severity score plus a list of identified, annotated mutations and their functional effects in VCF format. The best model performance is a ROC-AUC 0.899 for the model including patient age and ROC-AUC 0.83 for the model without patient age. AvailabilityCovidOutcome is freely available online under the URL https://www.covidoutcome.bio-ml.com as well as in a standalone version https://github.com/bio-apps/covid-outcome.
Kalcsevszki Regina、Horv¨¢th Andr¨¢s、Ligeti Bal¨¢zs、Pongor S¨¢ndor、Gy?rffy Bal¨¢zs
Faculty of Information Technology and Bionics, P¨¢zm¨¢ny P¨|ter Catholic UniversityFaculty of Information Technology and Bionics, P¨¢zm¨¢ny P¨|ter Catholic UniversityFaculty of Information Technology and Bionics, P¨¢zm¨¢ny P¨|ter Catholic UniversityFaculty of Information Technology and Bionics, P¨¢zm¨¢ny P¨|ter Catholic UniversityDepartment of Bioinformatics, Semmelweis University
医学研究方法生物科学研究方法、生物科学研究技术计算技术、计算机技术
Kalcsevszki Regina,Horv¨¢th Andr¨¢s,Ligeti Bal¨¢zs,Pongor S¨¢ndor,Gy?rffy Bal¨¢zs.CovidOutcome2: a tool for SARS-CoV2 mutation identification and for disease severity prediction[EB/OL].(2025-03-28)[2025-04-30].https://www.biorxiv.org/content/10.1101/2022.07.01.496571.点此复制
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