Evidence map›Paper›PMID 41669879›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long-Read Data.

Shuai Wang, Xuedong Wang, Mengyao Wang, Qian Zhou, Lusheng Wang, Shuai Cheng Li

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Shuai WangCity University of Hong Kong Shenzhen Research Institute, Shenzhen, China.ORCID https://orcid.org/0000-0002-1922-4878
Xuedong WangDepartment of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China.
Mengyao WangDepartment of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China.
Qian ZhouDepartment of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China.
Lusheng WangDepartment of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China.
Shuai Cheng LiCity University of Hong Kong Shenzhen Research Institute, Shenzhen, China.ORCID https://orcid.org/0000-0001-6246-6349

Funding

National Natural Science Foundation of China 32270687Shenzhen Science and Technology Program JCYJ20220818101201004
6 · The paper itself

Abstract

Long-read sequencing promises to unravel the complexity of polymorphic immune genes including HLA, KIR, IG, and TCR, yet existing tools fall short in accuracy and scope. Here, we present SpecImmune, the first unified computational framework to simultaneously genotype these genes alongside the intricate CYP family from long-read data. Employing an iterative graph-based haplotype reconstruction algorithm, SpecImmune delivers precise diploid assemblies for each locus from diverse data types. Validated on 1019 samples from the 1kGP ONT cohort, 42 PacBio CLR and 9 PacBio HiFi samples from HGSVC, and 47 PacBio HiFi plus 37 ONT samples from HPRC, SpecImmune achieved 98% four-field HLA typing accuracy, surpassing HLA*LA by 11% and SpecHLA by 12%. It also delivers robust KIR and germline IG/TCR genotyping and supports multi-locus CYP allele detection, positioning it among the first integrated long-read solutions across immune gene families. Beyond superior performance, SpecImmune uncovers elevated germline IG/TCR heterozygosity in African populations (

Indexed as

Histocompatibility TestingHLA AntigensPolymorphism, GeneticHaplotypesHigh-Throughput Nucleotide SequencingHumansHLA Antigensco‐evolutioncomplex gene typinggene sequence reconstructionimmunitylong‐read sequencing

Identifiers

PMID41669879
PMCPMC13088316

What OpenQuestion holds

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Registered trials

None linked

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.