ArticleNucleic acids research2018
geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 44 citations in OpenAlex.
- Article
- Systematic performance evaluation and application validation of an end-to-end NGS workstation.Scientific reports · 2026Article
- Complete Genome Sequencing of Occult Hepatitis B Virus in Hemodialysis Patients Reveals Subgenotype D2 and Immune Escape Mutations in Bangladesh.International journal of microbiology · 2026Article
- Addressing data management and analysis challenges in viral genomics: The Swiss HIV cohort study viral next generation sequencing database.PLOS digital health · 2025Article
- Hepatitis C Virus Saint Petersburg Variant Detection With Machine Learning Methods.Journal of medical virology · 2025Article
- Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models.PLoS computational biology · 2023Article
- Web Service for HIV Drug Resistance Prediction Based on Analysis of Amino Acid Substitutions in Main Drug Targets.Viruses · 2023Article
- Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data.Scientific reports · 2023Article
- Evolution of SIVmac239 following serial passaging in humanized mice.Journal of medical primatology · 2022Article
- First report of computational protein-ligand docking to evaluate susceptibility to HIV integrase inhibitors in HIV-infected Iranian patients.Biochemistry and biophysics reports · 2022Article
- A Genomic Information Management System for Maintaining Healthy Genomic States and Application of Genomic Big Data in Clinical Research.International journal of molecular sciences · 2022Review
- Simultaneous determination of HCV genotype and NS5B resistance associated substitutions using dried serum spots from São Paulo state, Brazil.Access microbiology · 2022Article
- Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction.Nucleic acids research · 2021Article
- Epidemiological data analysis of viral quasispecies in the next-generation sequencing era.Briefings in bioinformatics · 2021Review
- Treatment outcomes and costs of a simplified antiviral treatment strategy for hepatitis C among monoinfected and HIV and/or hepatitis B virus-co-infected patients in Myanmar.Journal of viral hepatitis · 2021Article
- Drug Resistance Spread in 6 Metropolitan Regions, Germany, 2001-2018Emerging infectious diseases · 2020Article
- Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing.Viruses · 2020Article
- Review
- Article
- Hotspots of Transmission Driving the Local Human Immunodeficiency Virus Epidemic in the Cologne-Bonn Region, Germany.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2019Article
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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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