| Literature DB >> 29718426 |
Matthias Döring1, Joachim Büch1, Georg Friedrich1, Alejandro Pironti1, Prabhav Kalaghatgi1, Elena Knops2, Eva Heger2, Martin Obermeier3, Martin Däumer4, Alexander Thielen4, Rolf Kaiser2, Thomas Lengauer1, Nico Pfeifer1,5,6.
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.Entities:
Mesh:
Year: 2018 PMID: 29718426 PMCID: PMC6031006 DOI: 10.1093/nar/gky349
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971