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] (<https://orcid.org/0000-0002-1390-0708>), Bruce Weir [ctb, ths] (<https://orcid.org/0000-0002-4883-1247>)|
|Bioconductor views||Genetics StatisticalMethod|
|Maintainer||Xiuwen Zheng <firstname.lastname@example.org>|
|URL||http://github.com/zhengxwen/HIBAG https://hibag.s3.amazonaws.com/index.html http://www.biostat.washington.edu/~bsweir/HIBAG|
|Package repository||View on Bioconductor|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.