Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers
Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-02-01
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| Series: | Viruses |
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| Online Access: | http://www.mdpi.com/1999-4915/8/2/53 |
| _version_ | 1819155374022852608 |
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| author | Jens Friis-Nielsen Kristín Rós Kjartansdóttir Sarah Mollerup Maria Asplund Tobias Mourier Randi Holm Jensen Thomas Arn Hansen Alba Rey-Iglesia Stine Raith Richter Ida Broman Nielsen David E. Alquezar-Planas Pernille V. S. Olsen Lasse Vinner Helena Fridholm Lars Peter Nielsen Eske Willerslev Thomas Sicheritz-Pontén Ole Lund Anders Johannes Hansen Jose M. G. Izarzugaza Søren Brunak |
| author_facet | Jens Friis-Nielsen Kristín Rós Kjartansdóttir Sarah Mollerup Maria Asplund Tobias Mourier Randi Holm Jensen Thomas Arn Hansen Alba Rey-Iglesia Stine Raith Richter Ida Broman Nielsen David E. Alquezar-Planas Pernille V. S. Olsen Lasse Vinner Helena Fridholm Lars Peter Nielsen Eske Willerslev Thomas Sicheritz-Pontén Ole Lund Anders Johannes Hansen Jose M. G. Izarzugaza Søren Brunak |
| author_sort | Jens Friis-Nielsen |
| collection | DOAJ |
| description | Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified. |
| first_indexed | 2024-12-22T15:35:57Z |
| format | Article |
| id | doaj.art-75912c2609a04407bf20a51d474a1a95 |
| institution | Directory Open Access Journal |
| issn | 1999-4915 |
| language | English |
| last_indexed | 2024-12-22T15:35:57Z |
| publishDate | 2016-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Viruses |
| spelling | doaj.art-75912c2609a04407bf20a51d474a1a952022-12-21T18:21:15ZengMDPI AGViruses1999-49152016-02-01825310.3390/v8020053v8020053Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple CancersJens Friis-Nielsen0Kristín Rós Kjartansdóttir1Sarah Mollerup2Maria Asplund3Tobias Mourier4Randi Holm Jensen5Thomas Arn Hansen6Alba Rey-Iglesia7Stine Raith Richter8Ida Broman Nielsen9David E. Alquezar-Planas10Pernille V. S. Olsen11Lasse Vinner12Helena Fridholm13Lars Peter Nielsen14Eske Willerslev15Thomas Sicheritz-Pontén16Ole Lund17Anders Johannes Hansen18Jose M. G. Izarzugaza19Søren Brunak20Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Kgs. Lyngby, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkDepartment of Autoimmunology and Biomarkers, Statens Serum Institut, DK-2300 Copenhagen S, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Kgs. Lyngby, DenmarkCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Kgs. Lyngby, DenmarkCentre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, DK-1350 Copenhagen, DenmarkCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Kgs. Lyngby, DenmarkCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, DK-2800 Kgs. Lyngby, DenmarkVirus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.http://www.mdpi.com/1999-4915/8/2/53sequence clusteringtaxonomic characterisationnovel sequence identificationnext generation sequencingcancer causing virusesoncovirusesassay contamination |
| spellingShingle | Jens Friis-Nielsen Kristín Rós Kjartansdóttir Sarah Mollerup Maria Asplund Tobias Mourier Randi Holm Jensen Thomas Arn Hansen Alba Rey-Iglesia Stine Raith Richter Ida Broman Nielsen David E. Alquezar-Planas Pernille V. S. Olsen Lasse Vinner Helena Fridholm Lars Peter Nielsen Eske Willerslev Thomas Sicheritz-Pontén Ole Lund Anders Johannes Hansen Jose M. G. Izarzugaza Søren Brunak Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers Viruses sequence clustering taxonomic characterisation novel sequence identification next generation sequencing cancer causing viruses oncoviruses assay contamination |
| title | Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers |
| title_full | Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers |
| title_fullStr | Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers |
| title_full_unstemmed | Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers |
| title_short | Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers |
| title_sort | identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers |
| topic | sequence clustering taxonomic characterisation novel sequence identification next generation sequencing cancer causing viruses oncoviruses assay contamination |
| url | http://www.mdpi.com/1999-4915/8/2/53 |
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