HIBAG

This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see HIBAG.

HLA Genotype Imputation with Attribute Bagging


Bioconductor version: 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 u.washington.edu>

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

Installation

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


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

BiocManager::install("HIBAG")

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

Documentation

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

browseVignettes("HIBAG")
HIBAG algorithm implementation HTML R Script
HIBAG vignette html HTML R Script
HLA association vignette html HTML R Script
Reference Manual PDF
NEWS Text

Details

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
URL https://github.com/zhengxwen/HIBAG https://hibag.s3.amazonaws.com/index.html
See More
Suggests parallel, ggplot2, reshape2, gdsfmt, SNPRelate, SeqArray, knitr, markdown, rmarkdown, Rsamtools
Linking To RcppParallel (>= 5.0.0)
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package HIBAG_1.40.0.tar.gz
Windows Binary (x86_64) HIBAG_1.40.0.zip (64-bit only)
macOS Binary (x86_64) HIBAG_1.40.0.tgz
macOS Binary (arm64) HIBAG_1.40.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/HIBAG
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/HIBAG
Bioc Package Browser https://code.bioconductor.org/browse/HIBAG/
Package Short Url https://bioconductor.org/packages/HIBAG/
Package Downloads Report Download Stats