Evidence map›Paper›PMID 38907895›Full record

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

Imputation-Based HLA Typing with GWAS SNPs.

Xiuwen Zheng, John Lee

Abstract read
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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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Xiuwen ZhengGenomics Research Center, AbbVie Inc., North Chicago, IL, USA. xiuwen.zheng@abbvie.com.
John LeeGenomics Research Center, AbbVie Inc., North Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SNP-based imputation approaches for human leukocyte antigen (HLA) typing take advantage of the haplotype structure within the major histocompatibility complex (MHC) region. These methods predict HLA classical alleles using dense SNP genotypes, commonly found on array-based platforms used in genome-wide association studies (GWAS). The analysis of HLA classical alleles can be conducted on current SNP datasets at no additional cost. Here, we describe the workflow of HIBAG, an imputation method with attribute bagging, to infer a sample's HLA classical alleles using SNP data. Two examples are offered to demonstrate the functionality using public HLA and SNP data from the latest release of the 1000 Genomes project: genotype imputation using pre-built classifiers in a GWAS, and model training to create a new prediction model. The GPU implementation facilitates model building, making it hundreds of times faster compared to the single-threaded implementation.

Indexed as

AllelesGenome-Wide Association StudyHistocompatibility TestingHLA AntigensPolymorphism, Single NucleotideSoftwareAlgorithmsComputational BiologyGenotypeHaplotypesHumansHLA Antigens1000 GenomesGWASHIBAGHLAImputationMHCSNP

Identifiers

PMID38907895

What OpenQuestion holds

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Read underepoch 390

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.