ArticleBMC bioinformatics2017
HLAscan: genotyping of the HLA region using next-generation sequencing data.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
60 citing papers in PubMed, 114 citations in OpenAlex.
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Association of HLA-I genotypic diversity with tumor mutational burden across cancer types in a large Chinese cohort.Discover oncology · 2026Article
- AI-powered mapping of tumor immunity for optimized mRNA vaccine engineering.Frontiers in oncology · 2026Review
- Evaluation of false positive and false negative errors in targeted next generation sequencing.Genome biology · 2025Article
- consHLA: a next generation sequencing consensus-based HLA typing workflow.BMC bioinformatics · 2025Article
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- Strategies for neoantigen screening and immunogenicity validation in cancer immunotherapy (Review).International journal of oncology · 2025Review
- Advances in Therapeutic Cancer Vaccines, Their Obstacles, and Prospects Toward Tumor Immunotherapy.Molecular biotechnology · 2025Review
- Spatial-Temporal Diversity of Extrachromosomal DNA Shapes Urothelial Carcinoma Evolution and Tumor Immune Microenvironment.Cancer discovery · 2025Article
- Ancient DNA HLA typing reveals significant shifts in frequency in Europe since the Neolithic.Scientific reports · 2025Article
- Article
- Vaccine approaches to treat urothelial cancer.Human vaccines & immunotherapeutics · 2024Review
- A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis.Computational and structural biotechnology journal · 2024Article
- Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing.BMC bioinformatics · 2024Article
- Association of HLA Haplotypes with Autoimmune Pathogenesis in Newly Diagnosed Type 1 Romanian Diabetic Children: A Pilot, Single-Center Cross-Sectional Study.Life (Basel, Switzerland) · 2024Article
- Article
- Germline homozygosity and allelic imbalance of HLA-I are common in esophagogastric adenocarcinoma and impair the repertoire of immunogenic peptides.Journal for immunotherapy of cancer · 2024Article
- Historical perspective and future directions: computational science in immuno-oncology.Journal for immunotherapy of cancer · 2024Review
- The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer's disease in APOEnpj aging · 2024Article
- Applications of genome sequencing as a single platform for clinical constitutional genetic testing.Genetics in medicine open · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSeveral recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data.
resultsHLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A, -B, and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing-based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, -B, -C, -DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%.
conclusionsHLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.