Covid-19 diagnosis by combining RT-PCR and pseudo-convolutional machines to characterize virus sequences.
Sci Rep
; 11(1): 11545, 2021 06 02.
Article
in English
| MEDLINE | ID: covidwho-1253983
ABSTRACT
The Covid-19 pandemic, a disease transmitted by the SARS-CoV-2 virus, has already caused the infection of more than 120 million people, of which 70 million have been recovered, while 3 million people have died. The high speed of infection has led to the rapid depletion of public health resources in most countries. RT-PCR is Covid-19's reference diagnostic method. In this work we propose a new technique for representing DNA sequences they are divided into smaller sequences with overlap in a pseudo-convolutional approach and represented by co-occurrence matrices. This technique eliminates multiple sequence alignment. Through the proposed method, it is possible to identify virus sequences from a large database 347,363 virus DNA sequences from 24 virus families and SARS-CoV-2. When comparing SARS-CoV-2 with virus families with similar symptoms, we obtained [Formula see text] for sensitivity and [Formula see text] for specificity with MLP classifier and 30% overlap. When SARS-CoV-2 is compared to other coronaviruses and healthy human DNA sequences, we obtained [Formula see text] for sensitivity and [Formula see text] for specificity with MLP and 50% overlap. Therefore, the molecular diagnosis of Covid-19 can be optimized by combining RT-PCR and our pseudo-convolutional method to identify DNA sequences for SARS-CoV-2 with greater specificity and sensitivity.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Computational Biology
/
Reverse Transcriptase Polymerase Chain Reaction
/
COVID-19 Nucleic Acid Testing
/
SARS-CoV-2
Type of study:
Diagnostic study
Limits:
Humans
Language:
English
Journal:
Sci Rep
Year:
2021
Document Type:
Article
Affiliation country:
S41598-021-90766-7
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