Bioconductor version: 2.5
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, Gary Wong
Maintainer: Nusrat Rabbee 
To install this package, start R and enter:
source("http:///biocLite.R")
biocLite("RLMM")    
| R Script | RLMM Doc | 
| biocViews | Microarray, OneChannel, SNP, GeneticVariability | 
| Depends | R, MASS | 
| Imports | |
| Suggests | |
| System Requirements | Internal files Xba.CQV, Xba.regions (or other regions file) | 
| License | LGPL (>= 2) | 
| URL | http://www.stat.berkeley.edu/users/nrabbee/RLMM | 
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 1.8.0 | 
| Package Source | RLMM_1.8.0.tar.gz | 
| Windows Binary | RLMM_1.8.0.zip (32- & 64-bit) | 
| MacOS 10.5 (Leopard) binary | RLMM_1.8.0.tgz | 
| Package Downloads Report | Download Stats | 
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