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Viral Tracing of Genetically Defined Neural Circuitry

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

ViTAL: Vision TrAnsformer based Low coverage SARS-CoV-2 lineage assignment.

Zuher Jahshan¹, Leonid Yavits¹

¹EnICS Labs, Engineering Department, Bar-Ilan University, Ramat Gan, Tel Aviv 5290002, Israel.

Bioinformatics (Oxford, England)

|February 20, 2024

Summary

ViTAL, a new deep learning tool, accurately assigns viral lineages from low-coverage genome sequencing data. This advancement improves viral surveillance and mutation tracking, crucial for managing infectious diseases like COVID-19.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

The rapid spread of viral diseases necessitates efficient surveillance of mutations and transmission dynamics.
Low-coverage whole-genome sequencing (LC-WGS) offers a scalable and cost-effective approach for viral genome sequencing.
However, LC-WGS reduces genomic detail, posing challenges for accurate viral lineage assignment.

Purpose of the Study:

To develop a novel deep learning algorithm for accurate viral lineage assignment from low-coverage genome sequencing data.
To enhance the capabilities of viral surveillance and mutation tracking for emerging infectious diseases.

Main Methods:

ViTAL (Viral lineage assignment) algorithm combines MinHash for feature extraction and Vision Transformer for classification.
The algorithm was evaluated across diverse coverage levels, including very low coverage (1×).
Performance was compared against state-of-the-art tools like UShER and Kraken2.

Main Results:

ViTAL achieved up to 87.7% lineage assignment accuracy at 1× coverage, significantly outperforming UShER (5.4%) and Kraken2 (27.4%).
ViTAL demonstrated comparable accuracy with up to 8× lower coverage than existing methods.
The algorithm showed proficiency in identifying lineages of novel genomes and aiding in preliminary phylogenetic placement of new variants.

Conclusions:

ViTAL provides a highly accurate and efficient solution for viral lineage assignment using low-coverage sequencing data.
This tool has the potential to significantly improve real-time viral surveillance and response strategies.
ViTAL's ability to handle novel variants underscores its utility in tracking the evolution of pathogens.