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HLA Genotype Imputation with Attribute Bagging

Bioconductor version: Release (3.19)

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.

Author: Xiuwen Zheng [aut, cre, cph] , Bruce Weir [ctb, ths]

Maintainer: Xiuwen Zheng <zhengx at>

Citation (from within R, enter citation("HIBAG")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

HIBAG algorithm implementation HTML R Script
HIBAG vignette html HTML R Script
HLA association vignette html HTML R Script
Reference Manual PDF


biocViews Genetics, Software, StatisticalMethod
Version 1.40.0
In Bioconductor since BioC 3.1 (R-3.2) (9.5 years)
License GPL-3
Depends R (>= 3.2.0)
Imports methods, RcppParallel
System Requirements C++11, GNU make
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Suggests parallel, ggplot2, reshape2, gdsfmt, SNPRelate, SeqArray, knitr, markdown, rmarkdown, Rsamtools
Linking To RcppParallel (>= 5.0.0)
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Source Package HIBAG_1.40.0.tar.gz
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macOS Binary (x86_64) HIBAG_1.40.0.tgz
macOS Binary (arm64) HIBAG_1.40.0.tgz
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