geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data

• Published in: Nucleic acids research Vol. 46; no. W1; pp. W271 - W277
• Main Authors: Döring, Matthias, Büch, Joachim, Friedrich, Georg, Pironti, Alejandro, Kalaghatgi, Prabhav, Knops, Elena, Heger, Eva, Obermeier, Martin, Däumer, Martin, Thielen, Alexander, Kaiser, Rolf, Lengauer, Thomas, Pfeifer, Nico
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 02.07.2018
• Subjects: Drug Resistance, Viral - genetics; Genome, Viral - genetics; Genotype; High-Throughput Nucleotide Sequencing; HIV Infections - drug therapy; HIV Infections - genetics; HIV Infections - virology; HIV-1 - genetics; Humans; Mutation; Software; Web Server Issue
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gky349

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.