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
|
HLA Genotype Imputation with Attribute Bagging
Bioconductor version: 3.2
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")
| HIBAG vignette pdf | ||
| HTML | HIBAG – an R Package for HLA Genotype Imputation with Attribute Bagging | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Genetics, Software, StatisticalMethod |
| Version | 1.6.0 |
| 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_1.6.0.tar.gz |
| Windows Binary | HIBAG_1.6.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | HIBAG_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | HIBAG_1.6.0.tgz |
| Subversion source | (username/password: readonly) |
| Git source | https://github.com/Bioconductor-mirror/HIBAG/tree/release-3.2 |
| Package Short Url | http://bioconductor.org/packages/HIBAG/ |
| Package Downloads Report | Download Stats |
Documentation »
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