Evidence map›Paper›PMID 38907894›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

NanoHLA: A Method for Human Leukocyte Antigen Class I Genes Typing Without Error Correction Based on Nanopore Sequencing Data.

Jidong Lang, Liu Qin

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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Jidong LangDepartment of Bioinformatics, Qitan Technology (Beijing) Co., Ltd, Beijing, China.
Liu QinDepartment of Bioinformatics, Qitan Technology (Beijing) Co., Ltd, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human leukocyte antigen (HLA) typing is of great importance in clinical applications such as organ transplantation, blood transfusion, disease diagnosis and treatment, and forensic analysis. In recent years, nanopore sequencing technology has emerged as a rapid and cost-effective option for HLA typing. However, due to the principles and data characteristics of nanopore sequencing, there was a scarcity of robust and generalizable bioinformatics tools for its downstream analysis, posing a significant challenge in deciphering the thousands of HLA alleles present in the human population. To address this challenge, we developed NanoHLA as a tool for high-resolution typing of HLA class I genes without error correction based on nanopore sequencing. The method integrated the concepts of HLA type coverage analysis and the data conversion techniques employed in Nano2NGS, which was characterized by applying nanopore sequencing data to NGS-liked data analysis pipelines. In validation with public nanopore sequencing datasets, NanoHLA showed an overall concordance rate of 84.34% for HLA-A, HLA-B, and HLA-C, and demonstrated superior performance in comparison to existing tools such as HLA-LA. NanoHLA provides tools and solutions for use in HLA typing related fields, and look forward to further expanding the application of nanopore sequencing technology in both research and clinical settings. The code is available at https://github.com/langjidong/NanoHLA .

Indexed as

AllelesHistocompatibility TestingNanopore SequencingComputational BiologyGenes, MHC Class IHigh-Throughput Nucleotide SequencingHistocompatibility Antigens Class IHLA AntigensHumansSequence Analysis, DNASoftwareHistocompatibility Antigens Class IHLA AntigensGenotypingHuman leukocyte antigenMHCNanoHLANanopore sequencing

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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.