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")
| Package source | RLMM_1.4.0.tar.gz |
|---|---|
| Windows binary | RLMM_1.4.0.zip |
| MacOS X 10.4 (Tiger) binary | RLMM_1.4.0.tgz |
| MacOS X 10.5 (Leopard) binary | RLMM_1.4.0.tgz |
| Package Downloads Report | Downloads Stats |
| biocViews | |
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| Depends |
R
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MASS
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| Imports | |
| Suggests | |
| System Requirements | 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 |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Development History | Bioconductor Changelog |