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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "HIBAG" in publications use:'
type: software
license: GPL-3.0-only
title: 'HIBAG: HLA Genotype Imputation with Attribute Bagging'
version: 1.41.1
abstract: Imputes HLA classical alleles using GWAS SNP data, and it relies on a training
  set of HLA and SNP genotypes. HIBAG can be used by researchers with published parameter
  estimates instead of requiring access to large training sample datasets. It combines
  the concepts of attribute bagging, an ensemble classifier method, with haplotype
  inference for SNPs and HLA types. Attribute bagging is a technique which improves
  the accuracy and stability of classifier ensembles using bootstrap aggregating and
  random variable selection.
authors:
- family-names: Zheng
  given-names: Xiuwen
  email: zhengx@u.washington.edu
  orcid: https://orcid.org/0000-0002-1390-0708
preferred-citation:
  type: article
  title: HIBAG -- HLA Genotype Imputation with Attribute Bagging
  authors:
  - family-names: Zheng
    given-names: Xiuwen
    email: zhengx@u.washington.edu
    orcid: https://orcid.org/0000-0002-1390-0708
  - family-names: Shen
    given-names: Judong
  - family-names: Cox
    given-names: Charles
  - family-names: Wakefield
    given-names: Jonathan
  - family-names: Ehm
    given-names: Margaret
  - family-names: Nelson
    given-names: Matthew
  - family-names: Weir
    given-names: Bruce
  journal: The Pharmacogenomics Journal
  year: '2014'
  url: https://www.nature.com/articles/tpj201318
repository: https://bioc.r-universe.dev
repository-code: https://github.com/zhengxwen/HIBAG
url: https://hibag.s3.amazonaws.com/index.html
date-released: '2024-05-13'
contact:
- family-names: Zheng
  given-names: Xiuwen
  email: zhengx@u.washington.edu
  orcid: https://orcid.org/0000-0002-1390-0708
references:
- type: article
  title: Imputation-Based HLA Typing with SNPs in GWAS Studies
  authors:
  - family-names: Zheng
    given-names: Xiuwen
  journal: Methods in Molecular Biology
  year: '2018'
  url: https://doi.org/10.1007/978-1-4939-8546-3_11