Show simple item record

dc.contributor.authorKleftogiannis, Den_US
dc.contributor.authorPunta, Men_US
dc.contributor.authorJayaram, Aen_US
dc.contributor.authorSandhu, Sen_US
dc.contributor.authorWong, SQen_US
dc.contributor.authorGasi Tandefelt, Den_US
dc.contributor.authorConteduca, Ven_US
dc.contributor.authorWetterskog, Den_US
dc.contributor.authorAttard, Gen_US
dc.contributor.authorLise, Sen_US
dc.coverage.spatialEnglanden_US
dc.date.accessioned2019-08-08T15:05:08Z
dc.date.issued2019-08-02en_US
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/31375105en_US
dc.identifier10.1186/s12920-019-0557-9en_US
dc.identifier.citationBMC Med Genomics, 2019, 12 (1), pp. 115 - ?en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3321
dc.identifier.eissn1755-8794en_US
dc.identifier.doi10.1186/s12920-019-0557-9en_US
dc.description.abstractBACKGROUND: Targeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs). METHODS: To address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection. RESULTS: Our tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments. CONCLUSIONS: AmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve .en_US
dc.format.extent115 - ?en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectCancer genomicsen_US
dc.subjectDeep sequencingen_US
dc.subjectError correctionen_US
dc.subjectIon torrenten_US
dc.subjectLiquid biopsiesen_US
dc.subjectNext generation sequencing (NGS)en_US
dc.subjectTargeted sequencingen_US
dc.subjectVariant callingen_US
dc.titleIdentification of single nucleotide variants using position-specific error estimation in deep sequencing data.en_US
dc.typeJournal Article
dcterms.dateAccepted2019-07-15en_US
rioxxterms.versionofrecord10.1186/s12920-019-0557-9en_US
rioxxterms.licenseref.startdate2019-08-02en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfBMC Med Genomicsen_US
pubs.issue1en_US
pubs.notesNot knownen_US
pubs.organisational-group/ICR
pubs.publication-statusPublished onlineen_US
pubs.volume12en_US
pubs.embargo.termsNot knownen_US
dc.contributor.icrauthorLise, Stefanoen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

http://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/