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IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome
BACKGROUND: Rapid analysis of SARS-CoV-2 genomic data plays a crucial role in surveillance and adoption of measures in controlling spread of Covid-19. Fast, inclusive and adaptive methods are required for the heterogenous SARS-CoV-2 sequence data generated at an unprecedented rate. RESULTS: We prese...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118100/ https://www.ncbi.nlm.nih.gov/pubmed/33985433 http://dx.doi.org/10.1186/s12859-021-04172-x |
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author | Desai, Sanket Rane, Aishwarya Joshi, Asim Dutt, Amit |
author_facet | Desai, Sanket Rane, Aishwarya Joshi, Asim Dutt, Amit |
author_sort | Desai, Sanket |
collection | PubMed |
description | BACKGROUND: Rapid analysis of SARS-CoV-2 genomic data plays a crucial role in surveillance and adoption of measures in controlling spread of Covid-19. Fast, inclusive and adaptive methods are required for the heterogenous SARS-CoV-2 sequence data generated at an unprecedented rate. RESULTS: We present an updated version of the SARS-CoV-2 analysis module of our automated computational pipeline, Infectious Pathogen Detector (IPD) 2.0, to perform genomic analysis to understand the variability and dynamics of the virus. It adopts the recent clade nomenclature and demonstrates the clade prediction accuracy of 92.8%. IPD 2.0 also contains a SARS-CoV-2 updater module, allowing automatic upgrading of the variant database using genome sequences from GISAID. As a proof of principle, analyzing 208,911 SARS-CoV-2 genome sequences, we generate an extensive database of 2.58 million sample-wise variants. A comparative account of lineage-specific mutations in the newer SARS-CoV-2 strains emerging in the UK, South Africa and Brazil and data reported from India identify overlapping and lineages specific acquired mutations suggesting a repetitive convergent and adaptive evolution. CONCLUSIONS: A novel and dynamic feature of the SARS-CoV-2 module of IPD 2.0 makes it a contemporary tool to analyze the diverse and growing genomic strains of the virus and serve as a vital tool to help facilitate rapid genomic surveillance in a population to identify variants involved in breakthrough infections. IPD 2.0 is freely available from http://www.actrec.gov.in/pi-webpages/AmitDutt/IPD/IPD.html and the web-application is available at http://ipd.actrec.gov.in/ipdweb/. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04172-x. |
format | Online Article Text |
id | pubmed-8118100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81181002021-05-14 IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome Desai, Sanket Rane, Aishwarya Joshi, Asim Dutt, Amit BMC Bioinformatics Software BACKGROUND: Rapid analysis of SARS-CoV-2 genomic data plays a crucial role in surveillance and adoption of measures in controlling spread of Covid-19. Fast, inclusive and adaptive methods are required for the heterogenous SARS-CoV-2 sequence data generated at an unprecedented rate. RESULTS: We present an updated version of the SARS-CoV-2 analysis module of our automated computational pipeline, Infectious Pathogen Detector (IPD) 2.0, to perform genomic analysis to understand the variability and dynamics of the virus. It adopts the recent clade nomenclature and demonstrates the clade prediction accuracy of 92.8%. IPD 2.0 also contains a SARS-CoV-2 updater module, allowing automatic upgrading of the variant database using genome sequences from GISAID. As a proof of principle, analyzing 208,911 SARS-CoV-2 genome sequences, we generate an extensive database of 2.58 million sample-wise variants. A comparative account of lineage-specific mutations in the newer SARS-CoV-2 strains emerging in the UK, South Africa and Brazil and data reported from India identify overlapping and lineages specific acquired mutations suggesting a repetitive convergent and adaptive evolution. CONCLUSIONS: A novel and dynamic feature of the SARS-CoV-2 module of IPD 2.0 makes it a contemporary tool to analyze the diverse and growing genomic strains of the virus and serve as a vital tool to help facilitate rapid genomic surveillance in a population to identify variants involved in breakthrough infections. IPD 2.0 is freely available from http://www.actrec.gov.in/pi-webpages/AmitDutt/IPD/IPD.html and the web-application is available at http://ipd.actrec.gov.in/ipdweb/. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04172-x. BioMed Central 2021-05-13 /pmc/articles/PMC8118100/ /pubmed/33985433 http://dx.doi.org/10.1186/s12859-021-04172-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Desai, Sanket Rane, Aishwarya Joshi, Asim Dutt, Amit IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome |
title | IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome |
title_full | IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome |
title_fullStr | IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome |
title_full_unstemmed | IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome |
title_short | IPD 2.0: To derive insights from an evolving SARS-CoV-2 genome |
title_sort | ipd 2.0: to derive insights from an evolving sars-cov-2 genome |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118100/ https://www.ncbi.nlm.nih.gov/pubmed/33985433 http://dx.doi.org/10.1186/s12859-021-04172-x |
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