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COVID-19 Genomic Sequences Analysis using Google Variant Transformation

Author(s)
Haroon Zeb Khan Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan
Muhammad Munwar Iqbal Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan
Muhammad Salman Bashir Department of Computer Science and IT, Virtual University of Pakistan, Pakistan
Abstract
Coronavirus genomics has been of various patterns since the pandemic began. The variants appear to differ in terms of both transmission and infection rates consistently. It analyzes genomic variants of coronaviruses to extract insights for research. This work employed the Variant Transform tool to process the Coronavirus variant caller format files with bigquery for genomic variant analysis enveloped on the Google Cloud Platform. We opted for Google Cloud Platform (GCP), particularly Google Cloud Life Sciences Suite with Free-tier Track. We downloaded genome sequences of COVID-19 and then transformed them into raw variant caller format files (VCF). Then analyzing COVID-19 VCF files by Google Variant Transforms tool. We have converted 30 coronavirus genomic sequences into Variant Caller format files using bioinformatics tools, then attained a table of coronavirus variant sites as variant residues through a big query and displayed the results with Data studio. Another part is Deep Variant's genetic analysis of non-viral genomic data, and its corresponding supported four model implementation. Our main breakthrough was storing Coronavirus Variant caller format files into big-query for Coronavirus Genomic analysis.
Publication Details
Page(s) 28-35
DOI DOI not available
Published Journal: Journal of Information Communication Technologies and Robotic Applications, Volume: 12, Issue: 1, Year: 2021

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Keywords
Coronavirus, Variant Transforms, Variant Caller Format, Big query, Genomic sequences
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