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HPV-EM: an accurate HPV detection and genotyping EM algorithm
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 algori...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459114/ https://www.ncbi.nlm.nih.gov/pubmed/32868873 http://dx.doi.org/10.1038/s41598-020-71300-7 |
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author | 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 |
author_facet | 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 |
author_sort | Inkman, Matthew J. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7459114 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74591142020-09-01 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 Sci Rep Article 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. Nature Publishing Group UK 2020-08-31 /pmc/articles/PMC7459114/ /pubmed/32868873 http://dx.doi.org/10.1038/s41598-020-71300-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article 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 HPV-EM: an accurate HPV detection and genotyping EM algorithm |
title | HPV-EM: an accurate HPV detection and genotyping EM algorithm |
title_full | HPV-EM: an accurate HPV detection and genotyping EM algorithm |
title_fullStr | HPV-EM: an accurate HPV detection and genotyping EM algorithm |
title_full_unstemmed | HPV-EM: an accurate HPV detection and genotyping EM algorithm |
title_short | HPV-EM: an accurate HPV detection and genotyping EM algorithm |
title_sort | hpv-em: an accurate hpv detection and genotyping em algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459114/ https://www.ncbi.nlm.nih.gov/pubmed/32868873 http://dx.doi.org/10.1038/s41598-020-71300-7 |
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