To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("RLMM")

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

RLMM

A Genotype Calling Algorithm for Affymetrix SNP Arrays

Bioconductor version: Release (2.14)

A classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now.

Author: Nusrat Rabbee <nrabbee at post.harvard.edu>, Gary Wong <wongg62 at berkeley.edu>

Maintainer: Nusrat Rabbee <nrabbee at post.harvard.edu>

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

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("RLMM")

Documentation

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

browseVignettes("RLMM")

 

PDF R Script RLMM Doc
PDF   Reference Manual

Details

biocViews GeneticVariability, Microarray, OneChannel, SNP, Software
Version 1.26.0
In Bioconductor since BioC 1.8 (R-2.3)
License LGPL (>= 2)
Depends R (>= 2.1.0)
Imports graphics, grDevices, MASS, stats, utils
Suggests
System Requirements Internal files Xba.CQV, Xba.regions (or other regions file)
URL http://www.stat.berkeley.edu/users/nrabbee/RLMM
Depends On Me
Imports Me
Suggests Me

Package Archives

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

Package Source RLMM_1.26.0.tar.gz
Windows Binary RLMM_1.26.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) RLMM_1.26.0.tgz
Mac OS X 10.9 (Mavericks) RLMM_1.26.0.tgz
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