To install this package, start R and enter:

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

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

RLMM

DOI: 10.18129/B9.bioc.RLMM    

This is the development version of RLMM; for the stable release version, see RLMM.

A Genotype Calling Algorithm for Affymetrix SNP Arrays

Bioconductor version: Development (3.6)

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:

## try http:// if https:// URLs are not supported
source("https://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 1.39.0
In Bioconductor since BioC 1.8 (R-2.3) (11.5 years)
License LGPL (>= 2)
Depends R (>= 2.1.0)
Imports graphics, grDevices, MASS, stats, utils
LinkingTo
Suggests
SystemRequirements Internal files Xba.CQV, Xba.regions (or other regions file)
Enhances
URL http://www.stat.berkeley.edu/users/nrabbee/RLMM
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package RLMM_1.39.0.tar.gz
Windows Binary RLMM_1.39.0.zip
Mac OS X 10.11 (El Capitan) RLMM_1.39.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RLMM
Package Short Url http://bioconductor.org/packages/RLMM/
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