COVID-19 Genomic Sequences Analysis using Google Variant Transformation

  • Haroon Zeb Khan Department of Computer Science, University of Engineering and Technology, Taxila
  • Muhammad Munwar Iqbal Department of Computer Science, University of Engineering and Technology, Taxila
  • Muhammad Salman Bashir Department of Computer Science and IT, Virtual University of Pakistan
Keywords: Big query, Coronavirus, Genomic sequences, Variant Transforms, Variant Caller Format

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 big-query 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.

Published
2021-06-30
How to Cite
[1]
H. Z. Khan, M. M. Iqbal, and M. S. Bashir, “COVID-19 Genomic Sequences Analysis using Google Variant Transformation”, jictra, pp. 28-35, Jun. 2021.
Section
Original Articles