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CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing

Next-generation sequencing (NGS) has revolutionized genetics and enabled the accurate identification of many genetic variants across many genomes. However, detection of biologically important low-frequency variants within genetically heterogeneous populations remains challenging, because they are di...

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Autores principales: Salehi, Faezeh, Baronio, Roberta, Idrogo-Lam, Ryan, Vu, Huy, Hall, Linda V., Kaiser, Peter, Lathrop, Richard H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333345/
https://www.ncbi.nlm.nih.gov/pubmed/25692681
http://dx.doi.org/10.1371/journal.pone.0116877
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author Salehi, Faezeh
Baronio, Roberta
Idrogo-Lam, Ryan
Vu, Huy
Hall, Linda V.
Kaiser, Peter
Lathrop, Richard H.
author_facet Salehi, Faezeh
Baronio, Roberta
Idrogo-Lam, Ryan
Vu, Huy
Hall, Linda V.
Kaiser, Peter
Lathrop, Richard H.
author_sort Salehi, Faezeh
collection PubMed
description Next-generation sequencing (NGS) has revolutionized genetics and enabled the accurate identification of many genetic variants across many genomes. However, detection of biologically important low-frequency variants within genetically heterogeneous populations remains challenging, because they are difficult to distinguish from intrinsic NGS sequencing error rates. Approaches to overcome these limitations are essential to detect rare mutations in large cohorts, virus or microbial populations, mitochondria heteroplasmy, and other heterogeneous mixtures such as tumors. Modifications in library preparation can overcome some of these limitations, but are experimentally challenging and restricted to skilled biologists. This paper describes a novel quality filtering and base pruning pipeline, called Complex Heterogeneous Overlapped Paired-End Reads (CHOPER), designed to detect sequence variants in a complex population with high sequence similarity derived from All-Codon-Scanning (ACS) mutagenesis. A novel fast alignment algorithm, designed for the specified application, has O(n) time complexity. CHOPER was applied to a p53 cancer mutant reactivation study derived from ACS mutagenesis. Relative to error filtering based on Phred quality scores, CHOPER improved accuracy by about 13% while discarding only half as many bases. These results are a step toward extending the power of NGS to the analysis of genetically heterogeneous populations.
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spelling pubmed-43333452015-02-24 CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing Salehi, Faezeh Baronio, Roberta Idrogo-Lam, Ryan Vu, Huy Hall, Linda V. Kaiser, Peter Lathrop, Richard H. PLoS One Research Article Next-generation sequencing (NGS) has revolutionized genetics and enabled the accurate identification of many genetic variants across many genomes. However, detection of biologically important low-frequency variants within genetically heterogeneous populations remains challenging, because they are difficult to distinguish from intrinsic NGS sequencing error rates. Approaches to overcome these limitations are essential to detect rare mutations in large cohorts, virus or microbial populations, mitochondria heteroplasmy, and other heterogeneous mixtures such as tumors. Modifications in library preparation can overcome some of these limitations, but are experimentally challenging and restricted to skilled biologists. This paper describes a novel quality filtering and base pruning pipeline, called Complex Heterogeneous Overlapped Paired-End Reads (CHOPER), designed to detect sequence variants in a complex population with high sequence similarity derived from All-Codon-Scanning (ACS) mutagenesis. A novel fast alignment algorithm, designed for the specified application, has O(n) time complexity. CHOPER was applied to a p53 cancer mutant reactivation study derived from ACS mutagenesis. Relative to error filtering based on Phred quality scores, CHOPER improved accuracy by about 13% while discarding only half as many bases. These results are a step toward extending the power of NGS to the analysis of genetically heterogeneous populations. Public Library of Science 2015-02-18 /pmc/articles/PMC4333345/ /pubmed/25692681 http://dx.doi.org/10.1371/journal.pone.0116877 Text en © 2015 Salehi et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Salehi, Faezeh
Baronio, Roberta
Idrogo-Lam, Ryan
Vu, Huy
Hall, Linda V.
Kaiser, Peter
Lathrop, Richard H.
CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing
title CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing
title_full CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing
title_fullStr CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing
title_full_unstemmed CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing
title_short CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing
title_sort choper filters enable rare mutation detection in complex mutagenesis populations by next-generation sequencing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333345/
https://www.ncbi.nlm.nih.gov/pubmed/25692681
http://dx.doi.org/10.1371/journal.pone.0116877
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