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.
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RLMM")
| Source | RLMM_1.0.0.tar.gz |
|---|---|
| Windows binary | RLMM_1.0.0.zip |
| OS X binary | RLMM_1.0.0.tgz |
| biocViews | |
|---|---|
| Depends | R, MASS |
| Suggests | |
| Imports | |
| SystemRequirements | Internal files Xba.CQV, Xba.regions (or other regions file) |
| License | LGPL version 2 or newer |
| URL | http://www.stat.berkeley.edu/users/nrabbee/RLMM |
| dependsOnMe | |
| suggestsMe |