AI Article Synopsis

  • * The geno2pheno[ngs-freq] web service was developed to quickly identify drug resistance in HIV-1 and HCV by processing frequency files instead of raw NGS data, significantly speeding up analysis.
  • * Users can upload frequency files to generate consensus sequences based on specific prevalence cutoffs, allowing them to predict resistance and make informed clinical decisions through the tool, which is accessible for free online.

Article Abstract

Identifying resistance to antiretroviral drugs is crucial for ensuring the successful treatment of patients infected with viruses such as human immunodeficiency virus (HIV) or hepatitis C virus (HCV). In contrast to Sanger sequencing, next-generation sequencing (NGS) can detect resistance mutations in minority populations. Thus, genotypic resistance testing based on NGS data can offer novel, treatment-relevant insights. Since existing web services for analyzing resistance in NGS samples are subject to long processing times and follow strictly rules-based approaches, we developed geno2pheno[ngs-freq], a web service for rapidly identifying drug resistance in HIV-1 and HCV samples. By relying on frequency files that provide the read counts of nucleotides or codons along a viral genome, the time-intensive step of processing raw NGS data is eliminated. Once a frequency file has been uploaded, consensus sequences are generated for a set of user-defined prevalence cutoffs, such that the constructed sequences contain only those nucleotides whose codon prevalence exceeds a given cutoff. After locally aligning the sequences to a set of references, resistance is predicted using the well-established approaches of geno2pheno[resistance] and geno2pheno[hcv]. geno2pheno[ngs-freq] can assist clinical decision making by enabling users to explore resistance in viral populations with different abundances and is freely available at http://ngs.geno2pheno.org.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031006PMC
http://dx.doi.org/10.1093/nar/gky349DOI Listing

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