Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences. Issue 12 (2nd December 2021)
- Record Type:
- Journal Article
- Title:
- Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences. Issue 12 (2nd December 2021)
- Main Title:
- Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences
- Authors:
- Ortuño, Francisco M
Loucera, Carlos
Casimiro-Soriguer, Carlos S
Lepe, Jose A
Camacho Martinez, Pedro
Merino Diaz, Laura
de Salazar, Adolfo
Chueca, Natalia
García, Federico
Perez-Florido, Javier
Dopazo, Joaquin - Abstract:
- Abstract: Background: The current SARS-CoV-2 pandemic has emphasized the utility of viral whole-genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and, therefore, useless sequences. Viral sequences evolve in the context of a complex phylogeny and different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data. Results: We have developed the impuSARS application, which takes advantage of the enormous number of SARS-CoV-2 genomes available, using a reference panel containing 239, 301 sequences, to produce missing data imputation in viral genomes. ImpuSARS was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing), showing great fidelity when reconstructing the original sequences, recovering the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (<20%). Conclusions: Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. ImpuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2Abstract: Background: The current SARS-CoV-2 pandemic has emphasized the utility of viral whole-genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and, therefore, useless sequences. Viral sequences evolve in the context of a complex phylogeny and different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data. Results: We have developed the impuSARS application, which takes advantage of the enormous number of SARS-CoV-2 genomes available, using a reference panel containing 239, 301 sequences, to produce missing data imputation in viral genomes. ImpuSARS was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing), showing great fidelity when reconstructing the original sequences, recovering the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (<20%). Conclusions: Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. ImpuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole-genome sequencing. … (more)
- Is Part Of:
- GigaScience. Volume 10:Issue 12(2021)
- Journal:
- GigaScience
- Issue:
- Volume 10:Issue 12(2021)
- Issue Display:
- Volume 10, Issue 12 (2021)
- Year:
- 2021
- Volume:
- 10
- Issue:
- 12
- Issue Sort Value:
- 2021-0010-0012-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12-02
- Subjects:
- Information storage and retrieval systems -- Research -- Periodicals
Biology -- Research -- Periodicals
Medical sciences -- Research -- Periodicals
Database management -- Periodicals
570.285 - Journal URLs:
- http://www.gigasciencejournal.com/ ↗
http://www.oxfordjournals.org/ ↗ - DOI:
- 10.1093/gigascience/giab078 ↗
- Languages:
- English
- ISSNs:
- 2047-217X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20234.xml