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dc.creatorEren, K
dc.creatorWeaver, S
dc.creatorKetteringham, R
dc.creatorValentyn, M
dc.creatorLaird Smith, M
dc.creatorKumar, V
dc.creatorMohan, S
dc.creatorKosakovsky Pond, SL
dc.creatorMurrell, B
dc.date.accessioned2020-12-11T21:19:46Z
dc.date.available2020-12-11T21:19:46Z
dc.date.issued2018-12-01
dc.identifier.issn1553-734X
dc.identifier.issn1553-7358
dc.identifier.doihttp://dx.doi.org/10.34944/dspace/4353
dc.identifier.other30543621 (pubmed)
dc.identifier.urihttp://hdl.handle.net/20.500.12613/4371
dc.description.abstract© 2018 Eren et al. http://creativecommons.org/licenses/by/4.0/. Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data. FLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN/dS) across time and across protein structure, and a phylogenetic tree browser. We demonstrate how FLEA may be used to process Pacific Biosciences HIV env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV env populations. A public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.
dc.format.extente1006498-e1006498
dc.language.isoen
dc.relation.haspartPLoS Computational Biology
dc.relation.isreferencedbyPublic Library of Science (PLoS)
dc.rightsCC BY
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectPhylogeny
dc.subjectSequence Alignment
dc.subjectSequence Analysis, DNA
dc.subjectSoftware
dc.subjectViruses
dc.titleFull-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons
dc.typeArticle
dc.type.genreJournal Article
dc.relation.doi10.1371/journal.pcbi.1006498
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.creator.orcidPond, Sergei L. Kosakovsky|0000-0003-4817-4029
dc.date.updated2020-12-11T21:19:42Z
refterms.dateFOA2020-12-11T21:19:47Z


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