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.
Package details |
|
---|---|
Author | Nusrat Rabbee <nrabbee@post.harvard.edu>, Gary Wong <wongg62@berkeley.edu> |
Bioconductor views | GeneticVariability Microarray OneChannel SNP |
Maintainer | Nusrat Rabbee <nrabbee@post.harvard.edu> |
License | LGPL (>= 2) |
Version | 1.52.0 |
URL | http://www.stat.berkeley.edu/users/nrabbee/RLMM |
Package repository | View on Bioconductor |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.