Identification of known and novel recurrent viral sequences in data from multiple patients and multiple cancers

• DOI: 10.7490/f1000research.1113095.1
• Publication Date: 2016-09-08
• Authors: Jens Friis-Nielsen; Kristín Rós Kjart...; Sarah Mollerup; Maria E. Asplund; Tobias Mourier; Randi Holm Jensen; Thomas Arn Hansen; Alba Rey‐Iglesia; Stine R. Richter; Ida Broman Nielsen; David E. Alquezar...; Pernille V. S. Olsen; Lasse Vinner; Helena Fridholm; Lars Peter Nielsen; Eske Willerslev; Thomas Sicheritz‐...; Ole Lund; Anders J. Hansen; José M. G. Izarzu...; Søren Brunak
• Keywords: Identification

Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association disease. Albeit effective in some cases, the fails detect novel pathogens and remote variants not present reference databases. We have developed species independent pipeline that utilises sequence clustering for identification of nucleotide sequences co-occur across multiple instances. applied workflow 686 libraries 252 cancer samples different tissue types, 32 non-template controls, 24 test samples. Recurrent were statistically associated biological, methodological or technical features with aim identify plausible contaminants may associate particular kit method. provide examples identified inhabitants healthy flora as well experimental contaminants. Unmapped statistical significance potentially represent unknown space can be identified.