@article{enlighten152134,
          volume = {7},
          number = {11},
           month = {November},
          author = {John Archer and Jan Weber and Kenneth Henry and Dane Winner and Richard Gibson and Lawrence Lee and Ellen Paxinos and Eric J. Arts and David L. Robertson and Larry Mimms and Miguel E. Qui{\~n}ones-Mateu},
           title = {Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism},
       publisher = {Public Library of Science},
         journal = {PLoS ONE},
            year = {2012},
             url = {https://eprints.gla.ac.uk/152134/},
        abstract = {HIV-1 coreceptor tropism assays are required to rule out the presence of CXCR4-tropic (non-R5) viruses prior treatment with CCR5 antagonists. Phenotypic (e.g., Trofile?, Monogram Biosciences) and genotypic (e.g., population sequencing linked to bioinformatic algorithms) assays are the most widely used. Although several next-generation sequencing (NGS) platforms are available, to date all published deep sequencing HIV-1 tropism studies have used the 454? Life Sciences/Roche platform. In this study, HIV-1 co-receptor usage was predicted for twelve patients scheduled to start a maraviroc-based antiretroviral regimen. The V3 region of the HIV-1 env gene was sequenced using four NGS platforms: 454?, PacBio? RS (Pacific Biosciences), Illumina?, and Ion Torrent? (Life Technologies). Cross-platform variation was evaluated, including number of reads, read length and error rates. HIV-1 tropism was inferred using Geno2Pheno, Web PSSM, and the 11/24/25 rule and compared with Trofile? and virologic response to antiretroviral therapy. Error rates related to insertions/deletions (indels) and nucleotide substitutions introduced by the four NGS platforms were low compared to the actual HIV-1 sequence variation. Each platform detected all major virus variants within the HIV-1 population with similar frequencies. Identification of non-R5 viruses was comparable among the four platforms, with minor differences attributable to the algorithms used to infer HIV-1 tropism. All NGS platforms showed similar concordance with virologic response to the maraviroc-based regimen (75\% to 80\% range depending on the algorithm used), compared to Trofile (80\%) and population sequencing (70\%). In conclusion, all four NGS platforms were able to detect minority non-R5 variants at comparable levels suggesting that any NGS-based method can be used to predict HIV-1 coreceptor usage.},
             doi = {10.1371/journal.pone.0049602}
}