Novel NGS Pipeline for Virus Discovery from a Wide Spectrum of Hosts and Sample Types
ABSTRACT The study of the microbiome data holds great potential for elucidating the biological and metabolic functioning of living organisms and their role in the environment. Metagenomic analyses have shown that humans, along with e.g. domestic animals, wildlife and arthropods, are colonized by an immense community of viruses. The current Coronavirus pandemic (COVID-19) heightens the need to rapidly detect previously unknown viruses in an unbiased way. The increasing availability of metagenomic data in this era of next-generation sequencing (NGS), along with increasingly affordable sequencing technologies, highlight the need for reliable and comprehensive methods to manage such data. In this article, we present a novel stand-alone pipeline called LAZYPIPE for identifying both previously known and novel viruses in host-associated or environmental samples and give examples of virus discovery based on it. LAZYPIPE is a Unix-based pipeline for automated assembling and taxonomic profiling of NGS libraries implemented as a collection of C++, Perl, and R scripts..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 30. Sept. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Plyusnin, Ilya [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2020.05.07.082107 |
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| PPN (Katalog-ID): |
XBI017772605 |
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| 520 | |a ABSTRACT The study of the microbiome data holds great potential for elucidating the biological and metabolic functioning of living organisms and their role in the environment. Metagenomic analyses have shown that humans, along with e.g. domestic animals, wildlife and arthropods, are colonized by an immense community of viruses. The current Coronavirus pandemic (COVID-19) heightens the need to rapidly detect previously unknown viruses in an unbiased way. The increasing availability of metagenomic data in this era of next-generation sequencing (NGS), along with increasingly affordable sequencing technologies, highlight the need for reliable and comprehensive methods to manage such data. In this article, we present a novel stand-alone pipeline called LAZYPIPE for identifying both previously known and novel viruses in host-associated or environmental samples and give examples of virus discovery based on it. LAZYPIPE is a Unix-based pipeline for automated assembling and taxonomic profiling of NGS libraries implemented as a collection of C++, Perl, and R scripts. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
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| 700 | 1 | |a Kant, Ravi |0 (orcid)0000-0003-3878-9775 |4 aut | |
| 700 | 1 | |a Jääskeläinen, Anne J. |4 aut | |
| 700 | 1 | |a Sironen, Tarja |4 aut | |
| 700 | 1 | |a Holm, Liisa |4 aut | |
| 700 | 1 | |a Vapalahti, Olli |4 aut | |
| 700 | 1 | |a Smura, Teemu |4 aut | |
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