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HIBAG

HLA Genotype Imputation with Attribute Bagging

Bioconductor version: 3.23 · Package version: 1.48.2

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("HIBAG")

Details

MaintainerXiuwen Zheng <zhengx@u.washington.edu>
AuthorXiuwen Zheng [aut, cre, cph] (ORCID: <https://orcid.org/0000-0002-1390-0708>), Bruce Weir [ctb, ths] (ORCID: <https://orcid.org/0000-0002-4883-1247>)
LicenseGPL-3
URLhttps://github.com/zhengxwen/HIBAG, https://hibag.s3.amazonaws.com/index.html
System RequirementsGNU make
Downloads rank565
Source branchRELEASE_3_23
biocViewsGenetics, Software, StatisticalMethod

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageHIBAG_1.48.2.tar.gz
Windows binary (x86_64)HIBAG_1.48.2.zip
macOS binary (arm64)HIBAG_1.48.2.tgz
macOS binary (x86_64)HIBAG_1.48.2.tgz
Dependencies

Depends: R (>= 3.2.0)

Imports: methods, RcppParallel

LinkingTo: RcppParallel (>= 5.0.0)

Suggests: parallel, ggplot2, reshape2, gdsfmt, SNPRelate, SeqArray (>= 1.20.0), knitr, markdown, rmarkdown, Rsamtools

Reverse dependencies

Suggests Me (1): PONG2