To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("HIBAG")

In most cases, you don't need to download the package archive at all.

HIBAG

   

This package is for version 3.1 of Bioconductor; for the stable, up-to-date release version, see HIBAG.

HLA Genotype Imputation with Attribute Bagging

Bioconductor version: 3.1

It is a software package for imputing HLA types using SNP data, and 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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("HIBAG")

Documentation

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

browseVignettes("HIBAG")

 

PDF R Script HIBAG vignette pdf
HTML R Script HIBAG – an R Package for HLA Genotype Imputation with Attribute Bagging
PDF   Reference Manual
Text   NEWS

Details

biocViews Genetics, Software, StatisticalMethod
Version 1.4.0
In Bioconductor since BioC 3.1 (R-3.2) (1 year)
License GPL-3
Depends R (>= 2.14.0)
Imports methods
LinkingTo
Suggests parallel, BiocStyle, knitr, gdsfmt(>= 1.2.2), SNPRelate(>= 1.1.6)
SystemRequirements
Enhances
URL http://www.biostat.washington.edu/~bsweir/HIBAG/ http://github.com/zhengxwen/HIBAG
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source HIBAG_1.4.0.tar.gz
Windows Binary HIBAG_1.4.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) HIBAG_1.4.0.tgz
Mac OS X 10.9 (Mavericks) HIBAG_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/HIBAG/tree/release-3.1
Package Short Url http://bioconductor.org/packages/HIBAG/
Package Downloads Report Download Stats

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