Abstract

Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep-learning algorithm that accurately detects SARS-CoV-2 and other common RNA respiratory viruses from RNA-seq data. Using in silico data, PACIFIC recovers the presence and relative concentrations of viruses with > 99% precision and recall. PACIFIC accurately detects SARS-CoV-2 and other viral infections in 63 independent in vitro cell culture and patient datasets. PACIFIC is an end-to-end tool that enables the systematic monitoring of viral infections in the current global pandemic.

Details

Title
PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses
Author
Acera Mateos Pablo 1 ; Balboa, Renzo F 2 ; Easteal, Simon 2 ; Eyras Eduardo 3 ; Patel, Hardip R 2 

 Australian National University, John Curtin School of Medical Research, Canberra, Australia (GRID:grid.1001.0) (ISNI:0000 0001 2180 7477); EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, Australia (GRID:grid.1001.0) (ISNI:0000 0001 2180 7477) 
 Australian National University, John Curtin School of Medical Research, Canberra, Australia (GRID:grid.1001.0) (ISNI:0000 0001 2180 7477); Australian National University, National Centre for Indigenous Genomics, Canberra, Australia (GRID:grid.1001.0) (ISNI:0000 0001 2180 7477) 
 Australian National University, John Curtin School of Medical Research, Canberra, Australia (GRID:grid.1001.0) (ISNI:0000 0001 2180 7477); EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, Australia (GRID:grid.1001.0) (ISNI:0000 0001 2180 7477); IMIM - Hospital del Mar Medical Research Institute, Barcelona, Spain (GRID:grid.20522.37) (ISNI:0000 0004 1767 9005); Catalan Institution for Research and Advanced Studies, Barcelona, Spain (GRID:grid.425902.8) (ISNI:0000 0000 9601 989X) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2486620892
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.