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A Genotype Calling Algorithm for Affymetrix SNP Arrays

Bioconductor version: Release (3.18)

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 <nrabbee at post.harvard.edu>, Gary Wong <wongg62 at berkeley.edu>

Maintainer: Nusrat Rabbee <nrabbee at post.harvard.edu>

Citation (from within R, enter citation("RLMM")):


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if (!require("BiocManager", quietly = TRUE))


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RLMM Doc PDF R Script
Reference Manual PDF


biocViews GeneticVariability, Microarray, OneChannel, SNP, Software
Version 1.64.0
In Bioconductor since BioC 1.8 (R-2.3) (18 years)
License LGPL (>= 2)
Depends R (>= 2.1.0)
Imports graphics, grDevices, MASS, stats, utils
System Requirements Internal files Xba.CQV, Xba.regions (or other regions file)
URL http://www.stat.berkeley.edu/users/nrabbee/RLMM
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Source Package RLMM_1.64.0.tar.gz
Windows Binary RLMM_1.64.0.zip
macOS Binary (x86_64) RLMM_1.64.0.tgz
macOS Binary (arm64) RLMM_1.64.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RLMM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RLMM
Bioc Package Browser https://code.bioconductor.org/browse/RLMM/
Package Short Url https://bioconductor.org/packages/RLMM/
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