Vy-PER: eliminating false positive detection of virus integration events in next generation sequencing data
| Autor: | David Ellinghaus, Georg Hemmrich, Malte C. Rühlemann, Lars Wienbrandt, Silke Szymczak, Lars Kraemer, Sören Mucha, Michael Forster, Martin Stanulla, Andre Franke |
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| Přispěvatelé: | University of Zurich, Forster, Michael |
| Rok vydání: | 2014 |
| Předmět: |
Hepatitis B virus
viruses Virus Integration 610 Medicine & health Biology medicine.disease_cause Genome Virus DNA sequencing Herpesviridae Article False positive paradox medicine Humans False Positive Reactions Genetics 1000 Multidisciplinary Multidisciplinary Genome Human Liver Neoplasms Computational Biology High-Throughput Nucleotide Sequencing Sequence Analysis DNA Precursor Cell Lymphoblastic Leukemia-Lymphoma 3. Good health Germ Cells 10036 Medical Clinic Human genome Software |
| Zdroj: | Scientific Reports |
| ISSN: | 2045-2322 |
| Popis: | Several pathogenic viruses such as hepatitis B and human immunodeficiency viruses may integrate into the host genome. These virus/host integrations are detectable using paired-end next generation sequencing. However, the low number of expected true virus integrations may be difficult to distinguish from the noise of many false positive candidates. Here, we propose a novel filtering approach that increases specificity without compromising sensitivity for virus/host chimera detection. Our detection pipeline termed Vy-PER (Virus integration detection bY Paired End Reads) outperforms existing similar tools in speed and accuracy. We analysed whole genome data from childhood acute lymphoblastic leukemia (ALL), which is characterised by genomic rearrangements and usually associated with radiation exposure. This analysis was motivated by the recently reported virus integrations at genomic rearrangement sites and association with chromosomal instability in liver cancer. However, as expected, our analysis of 20 tumour and matched germline genomes from ALL patients finds no significant evidence for integrations by known viruses. Nevertheless, our method eliminates 12,800 false positives per genome (80× coverage) and only our method detects singleton human-phiX174-chimeras caused by optical errors of the Illumina HiSeq platform. This high accuracy is useful for detecting low virus integration levels as well as non-integrated viruses. |
| Databáze: | OpenAIRE |
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