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HPV-EM: an accurate HPV detection and genotyping EM algorithm.
Inkman, Matthew J; Jayachandran, Kay; Ellis, Thomas M; Ruiz, Fiona; McLellan, Michael D; Miller, Christopher A; Wu, Yufeng; Ojesina, Akinyemi I; Schwarz, Julie K; Zhang, Jin.
Afiliação
  • Inkman MJ; Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
  • Jayachandran K; Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
  • Ellis TM; Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
  • Ruiz F; Department of Computer Science, Washington University in St. Louis, St. Louis, MO, 63105, USA.
  • McLellan MD; Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, 63108, USA.
  • Miller CA; McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.
  • Wu Y; McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.
  • Ojesina AI; Computer Science and Engineering Department, University of Connecticut, Storrs, CT, 06269, USA.
  • Schwarz JK; Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
  • Zhang J; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
Sci Rep ; 10(1): 14340, 2020 08 31.
Article em En | MEDLINE | ID: mdl-32868873
ABSTRACT
Accurate HPV genotyping is crucial in facilitating epidemiology studies, vaccine trials, and HPV-related cancer research. Contemporary HPV genotyping assays only detect < 25% of all known HPV genotypes and are not accurate for low-risk or mixed HPV genotypes. Current genomic HPV genotyping algorithms use a simple read-alignment and filtering strategy that has difficulty handling repeats and homology sequences. Therefore, we have developed an optimized expectation-maximization algorithm, designated HPV-EM, to address the ambiguities caused by repetitive sequencing reads. HPV-EM achieved 97-100% accuracy when benchmarked using cell line data and TCGA cervical cancer data. We also validated HPV-EM using DNA tiling data on an institutional cervical cancer cohort (96.5% accuracy). Using HPV-EM, we demonstrated HPV genotypic differences in recurrence and patient outcomes in cervical and head and neck cancers.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Alphapapillomavirus / Genes Virais / Genótipo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Alphapapillomavirus / Genes Virais / Genótipo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Female / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: ENGLAND / ESCOCIA / GB / GREAT BRITAIN / INGLATERRA / REINO UNIDO / SCOTLAND / UK / UNITED KINGDOM