RLMM: A Genotype Calling Algorithm for Affymetrix SNP Arrays

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.

Getting started

Package details

AuthorNusrat Rabbee <[email protected]>, Gary Wong <[email protected]>
Bioconductor views GeneticVariability Microarray OneChannel SNP
MaintainerNusrat Rabbee <[email protected]>
LicenseLGPL (>= 2)
URL http://www.stat.berkeley.edu/users/nrabbee/RLMM
Package repositoryView on Bioconductor
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RLMM documentation built on Oct. 31, 2019, 7:50 a.m.